Machine learning has witnessed remarkable advancements in recent years. And as this technology has become more accessible and pervasive, it has quickly become a driving force behind many of the technological advancements we see today. From image and speech recognition to autonomous vehicles and healthcare diagnostics, this powerful subset of artificial intelligence is no longer just a thing of the future but a key player in the current tech landscape.

This rapid adoption of machine learning has also led to an explosion of career opportunities for machine learning engineers. Tech professionals with this unique skill set are in high demand, yet only 12 percent of businesses say the supply of people with these skills is adequate. As more and more engineers look to make the shift into this field — and more and more companies look to hire these talented professionals — it’s important to understand what the role of a machine learning engineer entails and what skills and expertise are needed to thrive.

By gaining a deeper understanding of the role of a machine learning engineer, hiring managers and tech professionals alike can better navigate the rapidly evolving tech landscape and take advantage of the endless opportunities machine learning offers. Whether you are looking to hire top talent or embark on a career in machine learning, this article will provide valuable insights and guidance to help you thrive in this exciting field.

What is Machine Learning?

Before we delve into the specifics of the machine learning engineer role, let’s start by defining what machine learning is and how it differs from other branches of artificial intelligence. At its core, machine learning is a subset of AI that focuses on enabling computers to learn and improve from data without being explicitly programmed.

Machine learning algorithms learn patterns and relationships from vast amounts of data, allowing systems to make predictions, identify trends, and solve complex problems. This ability to learn from data is what sets machine learning apart from traditional rule-based programming approaches.

It’s important to note that machine learning encompasses various techniques, and one prominent subset is deep learning. Deep learning, a specialization within machine learning, utilizes neural networks to simulate human decision-making. These networks consist of interconnected nodes or artificial neurons arranged in layers. They process data, extract features, and make predictions or classifications based on the patterns they learn.

The field of machine learning encompasses a wide range of algorithms and methodologies, including supervised learning, unsupervised learning, and reinforcement learning. Each approach has its own set of applications and techniques, catering to different types of problems and data.

The Role of a Machine Learning Engineer

Machine learning engineers are the driving force behind the development and implementation of machine learning models and algorithms. Their expertise lies in designing, training, and deploying these models to solve complex problems and extract insights from vast datasets. Let’s delve into the specific responsibilities and tasks that machine learning engineers undertake.

Data Preparation

One of the foundational tasks of a machine learning engineer is data preparation. This involves gathering, cleaning, and organizing large amounts of data in a way that is suitable for training machine learning models. Machine learning algorithms rely heavily on high-quality data, and the process of data preprocessing ensures that the data is in a usable format. This may involve tasks such as handling missing values, normalizing data, and transforming features.

Algorithm Design and Selection

Machine learning engineers are responsible for selecting or designing the most appropriate algorithms for the task at hand. They analyze the problem domain, the available data, and the desired outcomes to determine the best approach. This involves choosing the right type of algorithm, such as decision trees, support vector machines, or deep neural networks. Additionally, they must consider hyperparameter tuning, selecting appropriate loss functions, and optimization algorithms to train the models effectively.

Model Training and Evaluation

Once the algorithm is selected or designed, machine learning engineers train the models using the prepared data. They iterate through training cycles, adjusting the model’s parameters and hyperparameters to optimize its performance. They evaluate the model‘s performance using various metrics, such as accuracy, precision, recall, or F1 score. This evaluation helps assess the model’s effectiveness and guides further improvements or iterations.

Deployment and Integration

The final step in the machine learning engineer’s workflow is deploying the trained model in a production environment. This involves integrating the model into larger systems or applications, ensuring its compatibility and scalability. Machine learning engineers must address considerations such as real-time processing, efficient data storage, and handling new incoming data. They work closely with software engineers and DevOps teams to ensure smooth deployment and monitor the model’s performance in real-world scenarios.

Key Machine Learning Engineer Skills

To excel as a machine learning engineer, one must possess a combination of technical skills and domain knowledge. Let’s explore the essential skills and areas of expertise that contribute to success in this field.

Mathematics

A strong foundation in applied mathematics is crucial for understanding the underlying concepts of machine learning. Linear algebra, calculus, and probability theory are fundamental mathematical frameworks used in developing and analyzing machine learning algorithms. Knowledge of linear algebra helps in understanding matrix operations, while calculus is essential for optimization algorithms. Probability theory enables machine learning engineers to work with probabilistic models and make statistical inferences from data.

Programming

Proficiency in programming languages is a must-have skill for machine learning engineers. Python is a popular choice due to its rich ecosystem of libraries and frameworks specifically designed for machine learning tasks. Java and C++ are also used in certain contexts. Machine learning engineers should be comfortable writing clean, efficient, and scalable code. They should understand key concepts like object-oriented programming, data structures, and algorithms.

Data Handling and Visualization

Machine learning engineers work extensively with data sets of varying sizes and complexity. They need to be skilled in data handling, including data preprocessing, data augmentation, and feature engineering. Proficiency in data visualization tools, such as Power BI, Tableau, or Alteryx, is valuable for gaining insights from data and communicating findings effectively.

Deep Understanding of Neural Networks

Machine learning engineers should have a strong understanding of neural networks and their architectures. This includes knowledge of different types of neural networks like feedforward networks, convolutional neural networks, recurrent neural networks, and multilayer perceptrons. They need to understand activation functions, backpropagation, and regularization techniques. Deep learning frameworks like TensorFlow, PyTorch, and Keras are essential tools for implementing and training neural network models.

Problem Solving and Critical Thinking

Machine learning engineers must possess excellent problem-solving and critical-thinking abilities. They need to decompose complex problems into smaller, manageable components and develop creative solutions for each component. They must be able to analyze and interpret results, make informed decisions, and iterate on their approaches based on feedback and performance evaluations.

Industries Hiring Machine Learning Engineers

The demand for machine learning engineers has skyrocketed as organizations across various industries recognize the immense value that machine learning can bring to their operations. In HackerRank’s latest Developer Skills Report, machine learning dominated the list of most in-demand skills, second only to problem solving. Hiring for machine learning engineers is only expected to accelerate in 2023. Let’s explore some of the notable industries actively seeking machine learning engineers:

Technology Companies

Techn companies of all sizes and domains are investing heavily in machine learning. These companies utilize machine learning engineers to develop algorithms for image and speech recognition, natural language processing, recommendation systems, and intelligent chatbots. Technology giants like Google, Amazon, and Microsoft are at the forefront of machine learning innovation, but startups and smaller companies are also harnessing the power of machine learning to differentiate their products and services.

Finance and Banking

The finance and banking sector is leveraging machine learning to gain insights from vast amounts of financial data, detect fraudulent activities, and improve risk assessment models. Machine learning engineers in this industry develop predictive models for credit risk analysis, fraud detection, algorithmic trading, and personalized financial recommendations. The ability to analyze complex financial data and build robust predictive models is highly valued in this sector.

Healthcare and Life Sciences

The healthcare and life sciences industry is witnessing a revolution powered by machine learning. Machine learning engineers contribute to developing models for disease diagnosis, drug discovery, personalized medicine, and patient monitoring. They work with medical imaging data, genomics data, electronic health records, and clinical trial data to unlock valuable insights and improve patient outcomes. Machine learning is transforming healthcare by enabling more accurate diagnoses, efficient drug development, and precision medicine.

Transportation and Autonomous Systems

Transportation companies are embracing machine learning to develop self-driving vehicles and enhance transportation systems. Machine learning engineers in this industry work on algorithms for object detection, path planning, traffic prediction, and intelligent decision-making. They utilize real-time sensor data, such as lidar and radar, to enable autonomous vehicles to perceive their environment and make informed decisions. The transportation sector offers exciting opportunities for machine learning engineers to shape the future of mobility.

Other Industries

These industries represent just a fraction of the diverse sectors seeking machine learning engineers. Others, such as retail, e-commerce, manufacturing, energy, and entertainment, are also actively integrating machine learning into their operations to gain a competitive edge and unlock new possibilities.

It’s worth noting that machine learning engineers can also find opportunities in consulting firms and research institutions, where they contribute to cutting-edge projects, collaborate with domain experts, and drive innovation across various industries.

Key Takeaways

Machine learning engineers play a pivotal role in shaping the future of technology and innovation. Their expertise in designing, training, and deploying machine learning models allows organizations to extract insights from vast amounts of data, make accurate predictions, and automate complex tasks. As the demand for machine learning solutions continues to rise across industries, the role of machine learning engineers becomes increasingly vital.

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Mobile applications have revolutionized every aspect of our lives, becoming integral to the way we interact, work, and stay entertained. But behind every successful mobile app lies the expertise of mobile applications developers — individuals who possesses the technical skills and creativity to bring big ideas to life on our pocket-sized screens. 

As the demand for mobile apps continues to grow, the role of a mobile applications developer has become increasingly vital. These talented professionals are the driving force behind the creation and optimization of mobile applications that cater to diverse user needs and business objectives. They’re the architects of the digital experiences that seamlessly integrate into our daily lives, from communication and productivity to entertainment and e-commerce.

The responsibilities of a mobile applications developer go beyond merely writing code, though. They must collaborate closely with stakeholders, including product managers, designers, and quality assurance teams, to understand requirements, design intuitive interfaces, and deliver exceptional user experiences. Most importantly, they’re involved in every stage of the mobile app development life cycle, from ideation and design to development, testing, and deployment.

To thrive in this fast-paced and ever-evolving field, mobile applications developers must possess a unique set of skills and expertise. They need to stay abreast of the latest mobile technologies and trends, continuously refining their craft to meet the evolving demands of users and businesses. In this article, we’ll delve into the world of mobile app development and explore the role of a mobile applications developer, shedding light on their responsibilities and the key skills needed to excel in this dynamic field.

What Is a Mobile Applications Developer?

A mobile applications developer is a skilled tech professional responsible for designing, building, and maintaining mobile applications for various platforms such as iOS and Android. They possess a deep understanding of mobile technologies, programming languages, and frameworks that enable them to craft robust and user-friendly applications.

The primary goal of a mobile applications developer is to bring innovative ideas to life through functional and visually appealing mobile apps. They collaborate closely with product managers, designers, and other stakeholders to gather requirements and translate them into  applications that meet user needs and business goals.

The Mobile App Development Process

Creating a successful mobile app requires a systematic and well-defined development process. Mobile applications developers follow a series of stages to bring an idea from conception to a fully functional app. Let’s explore the typical mobile app development life cycle and the key stages involved.

1. Planning and Ideation

The first stage of the mobile app development process is planning and ideation. Mobile applications developers collaborate with stakeholders to understand the app’s purpose, target audience, and business objectives. They gather requirements, brainstorm ideas, and outline the app’s features and functionalities. This stage lays the foundation for the entire development process.

2. UI/UX Design

In the UI/UX design stage, mobile applications developers work closely with designers to create visually appealing and intuitive user interfaces. They translate wireframes and mockups into interactive designs, ensuring that the app’s layout, navigation, and visual elements align with the intended user experience. Attention to detail is paramount to deliver a seamless and engaging user interface.

3. Front-End and Back-End Development

Once the design phase is complete, mobile applications developers embark on the front-end and back-end development. They leverage their programming skills and knowledge of mobile app development frameworks to bring the app to life. The front-end development involves implementing the user interface and integrating interactive elements, while the back-end development focuses on building the server-side infrastructure that supports the app’s functionality and data management.

4. Testing and Quality Assurance

Testing and quality assurance are critical stages in mobile app development. Mobile applications developers conduct rigorous testing to identify and rectify any bugs, errors, or performance issues. They perform functional testing, usability testing, compatibility testing, and performance testing to ensure that the app works seamlessly across different devices, platforms, and scenarios. Thorough testing ensures a high-quality app that can meet the expectations of millions of users.

5. Deployment and Maintenance

Once the app has undergone thorough testing, it’s ready for deployment. Mobile applications developers prepare the app for release in the relevant app stores, such as the Apple App Store or Google Play Store. They ensure compliance with the platform’s guidelines and assist in the submission process. After deployment, they continue to monitor the app’s performance, collect user feedback, and release updates and bug fixes as necessary to maintain a smooth and reliable user experience.

Key Skills & Expertise for Mobile Applications Developers

To excel as a mobile applications developer, individuals need a diverse skill set that combines technical expertise, creativity, and a passion for innovation. Here, we explore some of the key skills and knowledge areas that are essential for success in the mobile app development field.

Proficiency in Programming Languages

Mobile applications developers must have a strong command of programming languages such as Java, Kotlin, Swift, or JavaScript, depending on the mobile platform they’re specializing in. They should be adept at writing clean, efficient, and maintainable code that powers the app’s functionality. Keeping up with language updates and best practices is crucial to ensure optimal app performance and compatibility.

Mobile App Development Frameworks

Familiarity with mobile app development frameworks is vital for mobile applications developers. Frameworks like React Native and Flutter allow developers to build cross-platform apps using a single codebase. Understanding these frameworks and their associated tools enables developers to optimize development time and ensure a consistent user experience across multiple platforms.

UI/UX Design

A solid grasp of user interface (UI) and user experience (UX) principles is indispensable for mobile applications developers. They should understand how to create visually appealing and user-friendly interfaces that enhance the app’s usability and engage users. Collaboration with UI/UX designers is crucial to deliver intuitive and aesthetically pleasing mobile apps.

Knowledge of Mobile Platforms and Guidelines

Mobile applications developers should have in-depth knowledge of the target mobile platforms, such as iOS and Android, including their specific guidelines and best practices. Understanding platform-specific design patterns, user interface elements, and navigation principles ensures that the app aligns with the platform’s standards and offers a seamless user experience.

API Integration

Mobile applications often rely on data from external sources and services. Proficiency in integrating APIs — or application programming interfaces — is essential for mobile applications developers. They should be able to work with RESTful APIs or other communication protocols to connect the mobile app with various services and retrieve data in real-time. API integration allows mobile apps to access functionalities such as social media login, payment gateways, location services, push notifications, and more.

Mobile applications developers need to understand how to interact with APIs, handle authentication and authorization, and parse data responses. They should be familiar with common API formats such as JSON and XML and know how to make HTTP requests to retrieve and send data securely.

Testing and Debugging

Thorough testing and debugging are critical for ensuring the quality and reliability of mobile applications. Mobile applications developers should be skilled in various testing techniques and tools to identify and fix bugs, performance issues, and compatibility problems. They should conduct both manual and automated testing to validate the app’s functionality and user experience across different devices and scenarios.

Problem Solving and Analytical Thinking

Mobile applications developers often encounter complex challenges and technical hurdles during the development process. Strong problem-solving skills and analytical thinking are essential to identify root causes, explore alternative solutions, and make informed decisions. The ability to break down problems into manageable components and find creative and efficient solutions is highly valued in this role.

Communication and Collaboration

Effective communication and collaboration skills are crucial for mobile applications developers. They need to work closely with designers, product managers, and other team members to understand requirements, exchange feedback, and ensure that the app aligns with the intended vision. Strong interpersonal skills facilitate effective teamwork and foster a positive and productive development environment.

Continuous Learning and Adaptability

The field of mobile app development is constantly evolving, with new technologies, platforms, and trends emerging regularly. Mobile applications developers must have a growth mindset and a commitment to continuous learning. They should stay updated with the latest industry developments, explore new tools and frameworks, and adapt to changing requirements to deliver cutting-edge mobile apps. This includes expanding their knowledge and skills by exploring emerging technologies such as augmented reality (AR), virtual reality (VR), or machine learning (ML) to incorporate innovative features into their applications.

Attention to Detail

Mobile applications developers must have a keen eye for detail to deliver high-quality apps. They should pay close attention to code quality, performance optimization, and user interface consistency. Thoroughness in testing and debugging is essential to ensure that the app functions flawlessly and provides a seamless user experience.

Industries Hiring Mobile Applications Developers

Mobile applications have become an integral part of our daily lives, revolutionizing various industries. The demand for skilled mobile applications developers continues to soar as companies across different sectors recognize the immense value of having a strong mobile presence. These are some of the key industries that are actively hiring mobile applications developers.

Technology Companies and Startups

Unsurprisingly, technology companies and startups are at the forefront of mobile app development. These companies are constantly innovating and seeking to create cutting-edge mobile experiences. From large tech giants to small startups, the need for talented mobile applications developers is abundant. They hire developers to build mobile apps that enhance their core products, offer new services, and drive user engagement.

E-commerce and Retail

The e-commerce and retail industry heavily relies on mobile apps to provide seamless and convenient shopping experiences to customers. Mobile applications developers in this industry work on apps that enable users to browse products, make purchases, track shipments, and receive personalized recommendations. E-commerce and retail companies recognize the importance of capturing mobile users and invest in developing user-friendly and feature-rich mobile apps.

Finance, Banking, and FinTech

Mobile applications have transformed the way we manage our finances and conduct banking transactions. Finance and banking institutions  and FinTech companies hire mobile applications developers to create secure and user-friendly banking apps. These apps allow customers to check account balances, transfer funds, pay bills, and access financial services conveniently from their mobile devices. Mobile applications developers in this sector must have a strong understanding of security protocols and compliance requirements.

Health and Fitness

The health and fitness industry has experienced a significant digital transformation with the proliferation of mobile apps. Mobile applications developers in this field work on health tracking apps, workout planners, meditation and mindfulness apps, and virtual personal training platforms. These apps help individuals monitor their fitness progress, access personalized training routines, and maintain a healthy lifestyle. Mobile applications developers play a vital role in improving people’s well-being through mobile technology.

Travel and Hospitality

The travel and hospitality industry has embraced mobile apps to enhance the overall travel experience for customers. Mobile applications developers collaborate with hotels, airlines, travel agencies, and booking platforms to develop travel apps that offer features like flight and hotel bookings, itinerary management, navigation guides, and personalized recommendations. These apps simplify the travel planning process and provide users with real-time information and seamless interactions.

These are just a few examples of the industries actively seeking mobile applications developers. However, the demand for mobile apps spans across various sectors, including entertainment, education, logistics, and more. As mobile technology continues to advance, the opportunities for mobile applications developers are expanding.

Key Takeaways

If you’re a hiring manager seeking talented mobile applications developers or a tech professional looking to explore job opportunities in mobile app development, be sure to visit HackerRank’s roles directory. It provides insights into the skills and expertise required for different tech roles — including mobile applications developers — and helps you stay informed about the evolving tech hiring landscape.

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Software engineering and software development are two of the most in-demand careers in the tech industry. And with the U.S. Bureau of Labor Statistics projecting the number of software jobs to increase by 25 percent over the next decade, demand for these skilled professionals will only grow. 

But there is often confusion between the roles of software engineers and software developers. While the two terms are often used interchangeably, they can actually refer to distinct roles with unique skill sets and responsibilities. Understanding the differences between software engineers and software developers is crucial for both hiring managers and early career professionals looking to navigate the industry. 

Whether you’re looking to hire a software engineer or software developer, or you’re interested in pursuing a career in software development, this article will help you gain a better understanding of the skills and responsibilities associated with each role, leaving you equipped to make more informed hiring decisions or chart a career path that aligns with your strengths and interests.

What is a Software Engineer?

A software engineer is a professional who applies engineering principles to the design, development, testing, and maintenance of software. The role of a software engineer is often focused on the bigger picture of a software system and typically involves a high degree of problem-solving, as well as collaboration with other members of a development team. 

Responsibilities of a Software Engineer

The responsibilities of a software engineer can vary depending on the size and scope of the organization they work for, as well as the specific project they are working on. However, some common responsibilities of a software engineer may include:

• Designing and developing software applications and systems
• Overseeing the strategic planning and management of software projects
• Working with stakeholders to ensure software requirements are met
• Writing and testing code to ensure software quality and reliability
• Collaborating with team members to solve technical challenges
• Writing automated tests to ensure software quality and reliability
• Conducting research and staying up-to-date on industry trends and best practices
• Designing and implementing algorithms to solve complex problems
• Participating in code reviews and providing feedback to colleagues

Unique Skills Required for a Software Engineering Role

Software engineering requires a unique set of skills that go beyond technical know-how. A software engineer must also be able to work well with others, communicate effectively, and think critically. Some of the key skills required for a software engineering role include:

• In-depth knowledge of programming languages, frameworks, tools and operating systems
• Familiarity with software engineering best practices and methodologies 
• The ability to apply engineering principles to software creation 
• Experience debugging software and systems

• Communication and collaboration skills
• Proficiency in advanced mathematics 
• Strong problem-solving abilities
• Project management skills 
• Leadership skills 

What is a Software Developer?

A software developer is a professional who is responsible for writing, testing and maintaining software code. The role of a software developer is primarily focused on the technical aspects of software development, such as coding and debugging. So, where a software engineer is often focused on the design, development and testing of entire computer systems, a software developer may focus more on specific applications or parts of the software. Many software developers even specialize in certain programming languages or types of development — like mobile, front-end or web — in order to set themselves apart in the job market and gain greater expertise in the tools of their trade. 

Responsibilities of a Software Developer

Just like with software engineers, the responsibilities of a software developer can vary depending on the organization they work for, as well as the specific project they are working on. However, some common responsibilities of a software developer may include:

• Writing, testing and debugging code for software applications
• Collaborating with other members of a development team to solve technical challenges
• Participating in code reviews and providing feedback to colleagues
• Staying up-to-date on industry trends and best practices
• Working with end-users to identify software needs and requirements
• ​​Writing automated tests to ensure software quality and reliability

Unique Skills Required for a Software Development Role

Software development requires a unique set of skills that are focused on technical abilities and attention to detail. While a software developer must be able to work well with others and communicate effectively, their primary focus is on writing high-quality code. Some of the key skills required for a software development role include:

• Strong coding skills in one or more programming languages
• Attention to detail and a focus on writing high-quality code
• Knowledge of software development best practices and methodologies
• Ability to connect the big picture to the smaller components of a system or application
• Familiarity with software testing and debugging processes
• Knowledge of algorithms and data structures 
• Time management skills
• Creativity

What are the Differences Between a Software Engineer and a Software Developer?

While the terms software engineer and software developer are often used interchangeably, there are noteworthy differences between the two roles.

Scope of Work

The primary distinction between software engineers and software developers is in the scope of their work. Software engineers focus on the big picture — the entire software development life cycle – from requirements planning and analysis to the testing and deployment of new software. They leverage their extensive knowledge of programming languages, computer operating systems, advanced mathematics, and software development best practices to determine the best way to build and maintain complex software systems. Software engineers focus on, for example, how, where, and what data is stored. Or what tools to use to ensure a smooth integration with the existing codebase. 

Software developers, on the other hand, focus on the “development” phase of the software development life cycle. Their work involves building the individual components of a software system — often components they have specialized knowledge in – like front-end or back-end systems or mobile applications. They work with engineers to understand the requirements and design specifications, and then implement them.

Think of it like a restaurant kitchen. Software engineers are like the head chefs, creating the menu, choosing ingredients that complement one another and determining the right methods for cooking and preparing the food. And software developers are like the line cooks. They take the head chef’s vision and bring it to life, executing the recipes to perfection.

Focus on Technical Skills

While both software engineers and software developers require strong technical skills, their different focuses lead to specialization in different skills.

Software engineers tend to be more involved in the early stages of software development, such as requirements gathering, system design, and architecture planning. This requires engineers to have greater proficiency in a range of programming languages, frameworks, tools, and operating systems, as well as a broad understanding of various methodologies, trends, and best practices. They need to know how all the moving parts will work together in order to design software systems that are scalable, maintainable and efficient. 

Software developers, on the other hand, tend to focus more on the coding and testing of smaller-scale projects and may work more closely with end-users to ensure the software meets their needs. While they may possess many of the same technical skills as an engineer, their knowledge tends to be more focused and specialized, giving them a deeper understanding of the limitations and possibilities of specific software tools or programming languages. They take an engineer’s design specifications and find the best way to implement them in the code.

Education and Training

Software development is often seen as a subset of software engineering, so when it comes to education and training, there can be a fair amount of overlap between software engineers and software developers. But the level of education and training required for these two roles can and often does differ. 

Given the broader scope of a software engineer’s work, they’re often required to have more comprehensive technical education. They learn how to apply engineering principles and the scientific method to the entire software development life cycle, and are educated in subjects like systems design and analysis, software validation and testing, and software architecture. Some companies may even require a bachelor’s or master’s degree in computer science, software engineering, or a related field. However, with the rise of engineering bootcamps and more accessible online learning resources, there are more opportunities than ever for engineers without traditional education backgrounds.

A software developer may choose to take a similar educational path as a software engineer, allowing them to work in either role, or specialize in a particular programming language or type of software development. While software developer roles are less likely to require a college degree, many developers still choose to pursue higher education for the strong skills foundation — and leg-up in the job search — that a degree can provide. However, given that software developers’ main focus is on writing high-quality code, they often need less education than an engineer, which can make it easier to get started in a career as a software developer — particularly for people who are self-taught or don’t have a traditional coding background. 

Job Titles and Roles

Another difference between software engineers and software developers is their job titles and roles within an organization. Software engineers are often seen as senior-level professionals who oversee the design and development of software systems and may be involved in managing other members of a development team. Software developers, on the other hand, are typically seen as entry- or mid-level professionals who are responsible for writing and testing code and may work under the guidance of a software engineer.

How to Choose the Right Role for Your Team

Despite these differences, the lines between software engineering and software development can sometimes be blurred, and many professionals have skills and experience in both areas. Many organizations use the terms interchangeably, and the roles and responsibilities of software engineers and software developers can overlap depending on the size and scope of the project they are working on. 

For hiring managers looking to add software professionals to their teams, the choice of which role to hire for will depend on the specific needs and goals of the organization, as well as the skills and experience of the candidates being considered. 

Remember: software engineers work on the macro-level, while software developers work on the micro-level. If the team is focused on large-scale and complex software development projects with multiple components and integrations, a software engineer may be the right choice. But if the team is focused on coding and testing, say, a new mobile application for an existing system, or needs someone with expertise in a specific programming language or framework, a software developer may be a better fit. 

The size of a company can also be a determining factor. Startups, for example, often operate with leaner teams, which means they need software engineers who can act as both engineer and developer. Enterprise businesses with more robust software teams generally have more resources available to hire both engineers and developers, which allows them to take advantage of the specialized knowledge developers can bring to the table. 

Key Takeaways

Whether you’re looking to hire software professionals or find your next great role, understanding the differences between a software engineer vs. a software developer can be the key to your long-term success. To learn more about the skills and competencies needed for a variety of technical roles and browse our library of up-to-date resources, check out HackerRank’s roles directory.

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In the vast and rapidly-evolving world of artificial intelligence, there is a group of professionals who possess a unique blend of technical prowess and creative ingenuity. These individuals are known as deep learning engineers, and they are at the forefront of designing and implementing cutting-edge machine learning algorithms that power everything from autonomous robots to voice recognition software.

Deep learning engineers must possess a keen eye for detail and an unwavering dedication to uncovering novel solutions to complex problems. Their work requires not only a mastery of the mathematical underpinnings of deep learning but also a creative approach to designing models that can learn from vast quantities of data.

At its core, the work of a deep learning engineer is about pushing the boundaries of what is possible with artificial intelligence, and helping to shape a world that is smarter, more efficient and more interconnected than ever before. But what exactly does a deep learning engineer do, and what skills do they need to thrive on the job? Let’s find out. 

What is Deep Learning?

Before diving into the role of a deep learning engineer, let’s first define what deep learning is. Simply put, deep learning is a subset of machine learning that uses neural networks to simulate human decision-making. These neural networks are comprised of layers of interconnected nodes that work together to analyze data, identify patterns, and make predictions.

Deep learning is a critical tool, driving advances in fields such as image and speech recognition, natural language processing, and even self-driving vehicles. It’s a powerful approach that allows machines to learn and improve from experience, making it an ideal solution for complex, data-intensive problems.

What Are a Deep Learning Engineer’s Responsibilities?

The primary responsibility of a deep learning engineer is to design and implement deep learning models that are effective and efficient. They work to create algorithms that can process large amounts of data and learn from it to make predictions or identify patterns. Some of the specific tasks a deep learning engineer might undertake include:

• Data Preparation: One of the most important tasks of a deep learning engineer is preparing the data that the model will learn from. This involves gathering, cleaning, and organizing large amounts of data in a way that is useful for the algorithm. 
• Algorithm Design: Deep learning engineers must design algorithms that can learn from the data provided. They must choose the right neural network architecture and select appropriate activation functions, loss functions, and optimization algorithms.
• Training and Evaluation: Once the algorithm is designed, the deep learning engineer must train the model using the prepared data. They will evaluate the model’s performance and make adjustments to the algorithm as needed.
• Deployment: Finally, the deep learning engineer must deploy the model in a production environment, ensuring that it can handle real-world data and that it is integrated into the larger system.

What Kinds of Companies Hire Deep Learning Engineers?

In 2017, the deep learning market was worth $2.28 billion, but by the end of 2023, that number is expected to grow to $18.16 billion. This growth has been driven largely by the increasing adoption of cloud-based services and large-scale generation of unstructured data, creating a surge in demand for deep learning solutions — and the talented engineers who know how to develop them. While companies across a range of industries are now exploring the opportunities deep learning can unlock, these are some of the most notable industries hiring for these roles.

• Technology Companies: Technology companies of all shapes and sizes are investing heavily in deep learning. They hire deep learning engineers to develop algorithms for image and speech recognition, natural language processing, and other applications.
• Finance and Healthcare Companies: Companies in the finance and healthcare industries are also investing in deep learning. They hire deep learning engineers to develop predictive models for fraud detection, credit risk analysis, and disease diagnosis.
• Transportation Companies: Transportation companies are investing in deep learning to develop autonomous vehicles. They hire deep learning engineers to develop algorithms for object detection, path planning, and decision-making.

Skills Needed to Excel in Deep Learning

To be successful as a deep learning engineer, one must have a combination of technical and soft skills. Some of the essential skills required to excel in this field are:

• Mathematics: Deep learning algorithms rely heavily on advanced mathematics, including linear algebra, calculus and probability theory. A deep learning engineer must have a strong understanding of these concepts.
• Programming: Deep learning engineers must be proficient in programming languages such as Python, Java, and C++. They must also be familiar with deep learning frameworks such as TensorFlow, PyTorch, and Keras.
• Data Handling: A deep learning engineer must be proficient in handling large datasets. They should know how to preprocess data, perform data augmentation, and use data visualization techniques. Deep learning engineers should be familiar with tools like Power BI, Tableau, and Alteryx.
• Neural Networks: Deep learning engineers must have a strong understanding of neural networks and their architectures. They must know how to choose the right network for a particular task, select appropriate activation functions and understand backpropagation.
• Problem Solving: Deep learning engineers must be adept at solving complex problems. They must be able to break down problems into smaller components and develop solutions to each component.

As you can see, the role of a deep learning engineer is complex and multifaceted, requiring a unique blend of technical and creative skills. These techies play a crucial role in developing cutting-edge machine learning algorithms that power many of the advanced technologies we see today, and with the growing demand for deep learning solutions across a range of industries, the need for talented deep learning engineers is only set to increase. Whether you’re looking to hire great tech talent or land your next role, it’s important to have a solid understanding of the expertise and experience required for the job.

Explore HackerRank’s roles directory to uncover key skills for a variety of technical roles and gain access to a library of resources designed to keep you up to date on the ever-changing tech hiring landscape.

This article was written with the help of AI. Can you tell which parts?

The post What Does a Deep Learning Engineer Do? Role Overview & Skill Expectations appeared first on HackerRank Blog.

In today’s technology landscape, cloud computing has become a ubiquitous presence. Roughly 94 percent of organizations use the cloud in some capacity, ranging from basic storage solutions to more complex platforms for application development, analytics, and artificial intelligence and machine learning initiatives. 

As workforces become increasingly distributed, and companies more keen to invest in these kinds of efforts, the demand for fast, flexible and accessible cloud services is only expected to grow. This is because technologies like AI and ML require massive amounts of computing power, storage and connectivity, which are often difficult to manage with traditional on-premise solutions. The cloud provides a scalable and cost-effective solution to this problem, enabling companies to quickly and easily deploy and manage the resources they need to stay ahead of the competition.

But building and maintaining these systems is a complex task that requires specialized knowledge and skills — and the ability to adapt to an industry that’s constantly evolving.  

That’s where cloud architects come in. 

What Are a Cloud Architect’s Responsibilities?

Cloud architects are responsible for designing and managing the cloud-based infrastructure and applications that make up a company’s computing system. They work to ensure that these systems operate efficiently and securely while meeting the specific needs of the organization. In essence, cloud architects are the conductors of the cloud, overseeing and coordinating all the moving parts to create a harmonious and effective system.

Designing and Implementing Cloud Infrastructure 

Cloud architects are responsible for designing, implementing, and managing the cloud infrastructure that meets the requirements of their organization. This includes selecting the appropriate cloud service provider, defining the cloud architecture, and setting up the necessary cloud resources.

Developing Cloud Strategies 

Cloud architects need to understand the business requirements and develop cloud strategies that align with them. They need to ensure that the cloud infrastructure is scalable, reliable , and cost-effective.

Managing Cloud Security 

Another important aspect of the cloud architect’s role is ensuring the security of the cloud infrastructure. This includes implementing security policies, monitoring the cloud infrastructure for security threats, and implementing security controls to mitigate risks.

Managing Cloud Operations

Cloud architects are also responsible for managing the day-to-day operations of the cloud infrastructure. This includes monitoring the performance of the cloud infrastructure, optimizing the infrastructure for efficiency, and ensuring that the infrastructure is highly available, which allows the system to keep functioning, even when some components fail.

Collaborating With Stakeholders

Cloud architects work closely with stakeholders to understand their requirements and ensure that the cloud infrastructure supports their goals. They need to communicate effectively with both technical and non-technical stakeholders and make sure everyone is on the same page.

What Kinds of Companies Hire Cloud Architects?

Cloud architects are in high demand, and organizations in various industries are searching for them. Many technology-focused companies like Amazon, Microsoft and Google require cloud architects to manage their cloud-based infrastructure. However, as cloud computing has increasingly replaced or supplemented on-premise data centers, companies outside the tech industry are now hiring cloud architects in greater and greater numbers, too. 

Healthcare organizations use cloud computing to store electronic health records and conduct medical research. Financial institutions utilize the cloud for online banking and financial analysis. Retail companies use cloud computing to store customer data and conduct e-commerce transactions. Essentially, any organization that needs to store, process or analyze data online can benefit from hiring a cloud architect.

Types of Cloud Architect Positions

There are many types of cloud architect roles, which can differ depending on experience, education and company size.

At the entry-level, a cloud architect may start as a Junior Cloud Architect or Cloud Solutions Architect, working on developing and testing cloud-based solutions. As they gain experience, cloud architects may move into senior-level roles such as: 

• Senior Cloud Architect
• Cloud Infrastructure Architect
• Cloud Security Architect
• Cloud Integration Architect

At the highest levels of an organization, cloud architects may take on leadership roles such as Chief Cloud Architect, Cloud Technical Director or Cloud Strategy Lead, where they are responsible for setting the overall cloud strategy and guiding the direction of the organization’s cloud-based solutions.

Cloud architects must stay up-to-date with the latest cloud technologies and best practices. They may even choose to specialize in a particular cloud platform such as AWS, Azure or Google Cloud, which can provide a competitive edge in the job market. 

Career outlook and earning potential for cloud architects can vary depending on factors such as industry, company size and experience. However, as more organizations move their operations to the cloud, demand for skilled cloud architects is expected to remain high.

Skills Needed to Become a Cloud Architect

Technical Skills

Technical skills are crucial for cloud architects to design, implement and manage complex cloud-based solutions. Some of the essential technical skills needed to be a successful cloud architect include:

• Cloud Computing Platforms: Cloud architects must have expertise in cloud platforms such as AWS, Azure and Google Cloud. They should be able to work with cloud-based services such as compute, storage, and database, and know how to select the right service to meet the business needs.
• Infrastructure-as-Code (IaC): IaC is a method of managing and provisioning infrastructure through code. Cloud architects should be familiar with tools like Terraform, AWS CloudFormation, and Azure Resource Manager to create and manage infrastructure and resources on the cloud.
• Automation: Automation is essential for managing cloud-based infrastructure at scale. Cloud architects should have experience with automation tools like Ansible, Chef or Puppet to automate provisioning, configuration and deployment.
• Networking: Cloud architects should have knowledge of cloud networking concepts such as virtual private clouds (VPCs), subnets, routing tables, load balancing, and security groups. They should be able to design and implement secure and scalable network architectures.
• Security: Cloud architects must have a strong understanding of cloud security concepts such as identity and access management (IAM), encryption, and data protection. They should be able to design and implement secure cloud architectures that meet compliance and regulatory requirements.
• Monitoring and Logging: Cloud architects should be able to set up and configure monitoring and logging tools such as CloudWatch, Azure Monitor, and Stackdriver to monitor cloud-based infrastructure and services. They should also be able to set up alerts and notifications to detect and respond to issues quickly.

Soft Skills

But technical skills aren’t the only competencies a cloud architect needs to succeed. On the soft skills side, a cloud architect should possess strong communication skills, problem-solving skills and the ability to work collaboratively with others. Collaboration is particularly important, as the role entails working closely with cross-functional teams, including developers, project managers and IT operations teams, to ensure successful implementation of cloud solutions. In addition, cloud architects need a strong understanding of business needs in order to design cloud-based solutions that actually meet them.

Certifications

Though not necessary, certifications can be a great way for cloud architects to validate their skills and accelerate career advancement. There are several cloud computing certifications available for cloud architects, offered by various cloud service providers and independent organizations. Some of the popular cloud certifications include:

• AWS Certified Solutions Architect – Associate/Professional: Offered by Amazon Web Services, these certifications validate the skills and knowledge needed to design and deploy scalable, fault-tolerant, and highly available systems on AWS.
• Microsoft Certified: Azure Solutions Architect Expert: This certification validates the skills and knowledge needed to design solutions that run on Azure, including compute, storage, networking and security — services that make up the building blocks of cloud architecture.
• Google Cloud Certified – Professional Cloud Architect: Offered by Google Cloud, this certification validates the skills and knowledge needed to design, develop and manage solutions on Google Cloud Platform.
• Certified OpenStack Administrator (COA): Offered by the OpenStack Foundation, this certification validates the skills and knowledge needed to operate and manage an OpenStack cloud infrastructure.
• CompTIA Cloud+: This vendor-neutral certification validates the skills and knowledge needed to understand cloud computing concepts, architectures and security, and to design and deploy cloud-based solutions.

As the world of cloud computing continues to evolve and become more sophisticated, so too will the skills cloud architects need. Whether you’re looking to hire great tech talent or land your next role, it’s important to have a solid understanding of the expertise and experience required for the job. Explore HackerRank’s roles directory to uncover key skills for a variety of technical roles and gain access to a library of resources designed to keep you up to date on the ever-changing tech hiring landscape.

The post What Does a Cloud Architect Do? Role Overview & Skill Expectations appeared first on HackerRank Blog.

Human beings have been analyzing data since the dawn of civilization. The drive to measure and study the world around us has proven pivotal for history’s greatest innovations. Now, as artificial intelligence accelerates the creation of data to unfathomable heights, the ability to analyze data will become increasingly vital.

Enter data analysts, the professionals responsible for collecting, processing, and analyzing data to provide insights that drive business decisions. 

Overview of Data Analytics

A data analyst’s primary role is to analyze data to uncover patterns, trends, and insights that can help businesses make informed decisions. They collect, clean, and organize data from various sources and use statistical analysis tools to create reports and visualizations that highlight key findings. Data analysts work closely with business stakeholders, such as marketing teams, product managers, and executives, to understand their requirements and provide them with data-driven recommendations.

On a more technical level, the core job responsibilities of data analysts include:

• Writing high-quality code
• Collecting, processing, cleaning, and organizing data
• Analyzing data to identify patterns and trends
• Creating data visualizations and dashboards 
• Presenting findings to stakeholders
• Conducting experiments and A/B tests
• Collaborating with cross-functional teams
• Keeping up-to-date with advancements in technology

What Kinds of Companies Hire Data Analysts?

Employers across every industry employ data analysts to unlock insights in their data. The top industries hiring data analysts include tech, finance, healthcare, ecommerce, and consulting firms.

Tech Companies

Companies such as Google, Microsoft, Amazon, and Facebook rely heavily on data analysis to improve their products and services.

Finance and Banking

Banks, investment firms, and insurance companies use data analysts to monitor and analyze financial data, make predictions and manage risk.

Healthcare

Hospitals, medical research institutions, and pharmaceutical companies hire data analysts to analyze patient data, clinical trial results, and research outcomes.

Retail and E-commerce

Retail and e-commerce companies hire data analysts to analyze customer behavior, sales data, and marketing trends to improve their products and services.

Government and Non-profit Organizations

Government agencies and non-profit organizations use data analysts to analyze large data sets and make data-driven decisions.

Manufacturing and Logistics

Manufacturing and logistics companies hire data analysts to optimize production processes, analyze supply chain data, and identify areas for cost reduction.

Types of Data Analyst Positions

Data analyst job titles vary widely, depending on experience, specialization, and industry. 

Early career-level professionals will typically start their career with an entry-level title like junior data analyst or data analyst I. They’ll typically work in that role for one to three years, gaining experience and domain expertise. 

A data analyst’s title may also vary depending on the industry they work in. Industry-specific job titles include:

• Business Intelligence Analyst
• Marketing Analyst
• Financial Analyst
• Healthcare Analyst
• Operations Analyst
• Data Science Analyst

From there, they may have the opportunity to move into more senior-level roles with more hands-on experience, such as senior data analyst or lead analyst. While they spend several years honing their skills, their responsibilities expand to include taking more ownership of projects, working independently in a team environment, and mentoring project team members. 

With some experience under their belt, a data analyst often faces a crossroads in their career. The first path is to pivot into people and team management functions, where hiring, mentoring, resource planning and allocation, strategy, and operations become a larger component of their role. The other possible career path is to continue as an individual contributor, where they can develop deeper technical expertise in various technology languages and frameworks.

Requirements to Become a Data Analyst

Programming Skills

Data analysts use several programming languages and frameworks to collect, process, analyze, and visualize data. The choice of programming language depends on the type of analysis required, the size and complexity of the data, and the individual preferences of the analyst.

Python

Python is one of the most popular programming languages for data analysis. It has a large and active user community and is widely used in scientific computing and data analysis. Python has several libraries and frameworks useful for data analysis, including Pandas, NumPy, Matplotlib, and Scikit-learn.

R

R is another popular programming language for data analysis. It has a comprehensive set of libraries and packages that make it ideal for statistical analysis and data visualization. R is particularly useful for working with large datasets and conducting advanced statistical analysis.

SQL

SQL (structured query language) is a programming language used to manage and manipulate relational databases. It is commonly used for data analysis, particularly in industries such as finance and healthcare, where data is stored in databases. SQL is useful for querying, manipulating, and aggregating data, and for creating complex reports and data visualizations.

MATLAB

MATLAB is a programming language commonly used for numerical computing, data analysis, and data visualization. It has a wide range of toolboxes and functions for signal processing, statistics, and machine learning. MATLAB is particularly useful for scientific computing and data analysis in fields such as engineering and finance.

Julia

Julia is a high-performance programming language designed for numerical and scientific computing. It has a simple syntax and is easy to use for data analysis, machine learning, and other scientific applications. Julia is particularly useful for working with large datasets and conducting complex statistical analysis.

D3.js

D3.js is a JavaScript library for creating interactive visualizations. It provides a powerful set of tools for creating complex and dynamic visualizations that can be integrated with web applications. D3.js is particularly useful for creating custom visualizations that are not easily achievable with other frameworks.

Technical Tools

Tableau

Tableau is a popular data visualization tool that allows users to create interactive dashboards and reports. It provides a wide range of built-in visualization options and a drag-and-drop interface for creating custom visualizations.

Excel

Microsoft Excel is a powerful tool that data analysts use for a variety of tasks. Some of the ways data analysts use Excel include:

• Data cleaning
• Data visualization
• Data analysis
• Pivot tables
• Macros

Power BI

Microsoft’s Power BI is a powerful data visualization and business intelligence tool that’s tightly integrated with Excel. Data analysts use Power BI to analyze data, create interactive dashboards, and share insights with others. 

SAS

SAS (Statistical Analysis System) is a software suite that data analysts use to manage, analyze, and report on data. Key functionalities in SAS include data management, statistical analysis, data visualization, machine learning, and reporting.

Mathematics & Statistics

Beyond programming, data analysts also need to be skilled in mathematics and statistics. Competency in the following subjects is key:

• Linear Algebra
• Calculus
• Probability
• Classification 
• Regression
• Clustering

Soft Skills

Technical competency alone isn’t enough to succeed in a data analyst role. Soft skills are a must in any data analysis role, Soft skills that are important for data analysts include:

• Time management
• Communication
• Presentation
• Project management
• Creativity
• Problem solving

Experience & Education

After competency, the most important qualification for data analysts is experience. For most employers, on-the-job experience and training is a critical requirement.

Then, there’s the question of education. 65% of data analysts have a bachelor’s degree, and 15% have a master’s degree. If you’re hiring data analysts, there’s a high likelihood that many of them will have a degree. And many companies still require data analysts to hold four-year degrees. However, many employers are broadening their candidate searches by prioritizing real-world skills.

The post What Does a Data Analyst Do? Role Overview & Skill Expectations appeared first on HackerRank Blog.

Despite being less than two decades old, DevOps plays a vital role in the software development industry. Today, 77% of organizations rely on DevOps to deploy software. Unsurprisingly, this has led to DevOps engineer becoming the seventh most in-demand job in the world. In this post, we break down the statistics, job requirements, and responsibilities of a career in DevOps engineering.

What Is DevOps?

DevOps balances software development and IT operations to support continuous integration and continuous delivery (CI/CD). It’s a methodology with a goal to keep an entire organization working together seamlessly, with agile processes and systems. DevOps allows businesses to create and release updates to their services and products faster than traditional development models. When done well, this means you can deploy code multiple times daily.

What Does a DevOps Engineer Do?

A DevOps engineer is responsible for managing and maintaining code, application maintenance, as well as application management. They work with a variety of experts in different departments to coordinate the design, development, testing, release, and lifecycle management of software and applications.

A DevOps engineer is responsible for any number of tasks related to:

• Project management
• Writing, editing, and coordinating code and review
• System performance testing and maintenance
• Prototyping features and solutions
• Server administration

What Kinds of Companies Hire DevOps Engineers?

Any company that creates software or applications needs DevOps engineers to manage their operations. With companies in every industry becoming increasingly driven by technology, the demand and opportunities for professionals with this skill set continues to grow. The top sectors employing DevOps engineers include:

• Fortune 500: 29%
• Technology: 17%
• Finance: 12%
• Retail: 8%
• Professional Services: 6%
• Telecommunication: 4%
• Manufacturing: 4%
• Insurance: 4%
• Healthcare: 3%

Types of DevOps Engineer Positions

The titles DevOps engineers hold vary drastically, depending on their experience, education, and company. At the beginning of their career, a DevOps engineer will start out with an entry-level role, like junior DevOps engineer or DevOps engineer I. A new DevOps engineer usually works in one of these roles for one to three years.

From there, they’ll have the opportunity to move into more senior-level and specialized roles with hands-on engineering experience. DevOps engineering job titles include: 

• DevOps software developer
• DevOps engineer
• DevOps evangelist
• Automation architect
• Cloud DevOps engineer
• Senior DevOps engineer

While they spend several years honing their skills, their responsibilities expand to include taking ownership of projects, working independently in a team environment, and mentoring project team members.

After gaining more experience, a DevOps engineer often faces a crossroads in their career having to choose between a few paths. 

The first path is to pivot into people and team management functions. Hiring, mentoring, resource planning and allocation, strategy, and operations become a larger component of the responsibilities of DevOps professionals pursuing this career path. At the higher levels of an organization, these job functions might include:

• DevOps engineering manager
• Director of DevOps
• Chief Information Officer (CIO)
• Chief Technology Officer (CTO)

The second possible career path is to continue as an individual contributor. Many DevOps engineers opt to continue their careers as individual contributors, enjoying equally fulfilling careers and developing deeper technical expertise in various languages and frameworks.

The third possible career path is to transition out of DevOps into a related field, such as software development, business analysis, or product management. Because the responsibilities of DevOps intersect with multiple technical disciplines, DevOps engineers are well-positioned to transition to a career in a different field that interests them.

Salary Comparisons and Job Outlook

Estimates of the average annual salary for a DevOps engineer range from $99,527 to $128,387. An entry-level DevOps engineer can earn an average salary of $67,000 while a DevOps engineer later in their career (over 20 years of experience) can average $143,000 annually. This doesn’t factor in bonuses, stock options, and other cash incentives that can add to total compensation.

While we don’t have data on the growth rate of DevOps engineers specifically, the U.S. Bureau of Labor Statistics does include this role in its overall data for software developers. Software developer employment is projected to grow 25 percent through 2031 — more than triple the average for all occupations.

Requirements to Become a DevOps Engineer

Technical Skills

DevOps engineers use a range of programming languages to deliver software. These include, to name a few:

• Python
• Java
• JavaScript
• Go
• PHP
• PERL
• Ruby
• TypeScript

A core requirement of DevOps is expertise in the technologies offered by cloud-hosting providers. These include, to name a few:

• AWS
• Azure
• GCP
• IBM Cloud
• Oracle Cloud

Typically, DevOps engineers are expected to have familiarity with a wide range of development tools, including:

• CI/CD (Bamboo, GitLap, Buddy)
• Virtualization (Kubernetes, Docker)
• Version control (examples: GitHub, Jenkins)
• Monitoring and analytics (Nagios, Prometheus, Zabbix)
• Deployment automation (Red Hat Ansible)
• Cloud computing (Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure)
• Network protocols (TCP, UDP)
• Technical support

DevOps is a constantly evolving field, so it’s important to do research specific to the industries and roles you’re applying to or hiring for to understand specific technical competencies.

Soft Skills

Technical competency alone isn’t enough to succeed in a DevOps engineering role. Analytical, mathematical, and problem-solving skills are a must in any technical job. And in a digital-only or remote first environment, soft skills are even more critical.

Employers may prefer engineers with strong soft skills, such as:

• Problem solving
• Communication
• Project management
• Time management
• Creativity

Experience

After technical skills, the most important qualification for DevOps engineers is experience. On-the-job experience and training is a critical requirement for many employers.

Then, there’s the question of education. The education requirements for DevOps positions vary widely. In the U.S., the vast majority of DevOps engineers have a college education, with 75% having a bachelor’s degree, and 20% having a master’s. 

Many companies still require developers to have a four-year degree. While hiring developers, it’s likely that many of them will have a degree. However, competition for skilled software engineers is high, and it’s not uncommon for job openings with a degree requirement to go unfilled. Ultimately, employers that prioritize real-world skills over pedigree gain access to a larger volume of skilled DevOps talent.

Resources for Hiring DevOps Engineers

Developer Hiring Solutions

The Ultimate Hiring Guide to Developer Skills & Roles

[Checklist] How to Hire the Right DevOps Talent for Your Company

The post What Does a DevOps Engineer Do? Job Overview and Skill Expectations appeared first on HackerRank Blog.

In 2021, the size of the global cloud computing market was valued at $445.3 billion. And it’s expected to grow to $947.3 billion by 2026. That’s a blistering growth rate of 112.7 percent in just five years.

However, the tech industry is facing a huge deficit in the number of skilled cloud engineers available to build this growing industry. If left unchecked, this hiring gap could hinder the growth and innovation of the cloud computing industry writ large. 

In this post, we’ll break down the statistics, job requirements, and responsibilities of a career in cloud engineering.

Overview of the Duties of a Cloud Engineer

Companies of every size and industry are racing to the cloud. Cloud computing is a service that provides on-demand access to computer system resources without direct management or ownership by the party using the service. These services include computing power, data storage, platforms, infrastructure, and software.

Cloud engineers are IT professionals responsible for a company’s cloud computing infrastructure, including design, implementation, maintenance, and support.

Cloud engineers will work in a variety of cloud environments, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

On a more technical level, the core job responsibilities of cloud engineers include:

• Writing highly scalable, testable code
• Building cloud environments on cloud infrastructure platforms
• Configuring cloud infrastructure components including networking and security services
• Discovering and fixing programming bugs
• Presenting and demonstrating features to internal and external stakeholders
• Keeping up-to-date with advancements in technology
• Working in an agile environment

What Kinds of Companies Hire Cloud Engineers?

Any company that’s looking to build cloud infrastructure or migrate their existing systems to the cloud will need to hire cloud engineers. As companies of every size transition to the cloud, the industries that cloud engineers work in continue to expand.

This trend was already well underway, but it was dramatically accelerated by the COVID-19 pandemic and prolonged global lockdowns. Overnight, a majority of the world’s work, education, and entertainment shifted online, leading to a dramatic spike in the demand for platforms, databases, and technologies supported by the cloud. This has left many companies struggling to find the cloud engineers they need to scale in a remote-first world. 

Retail, entertainment, software, consulting, financial services, defense, education, fintech, telecommunications, healthcare — the demand (and opportunity) for cloud engineering is nearly endless. 

In addition to the companies hiring engineers for their in-house teams, Microsoft, Amazon, and Google employ thousands of cloud engineers to work on their infrastructure as a service (IaaS), platform as a service (PaaS), and serverless computing environments.

Unsurprisingly, this growth in the demand and applications for cloud computing has had a direct impact on company hiring needs and the career outlook of cloud engineering.

In 2020, there were 775,022 cloud computing jobs posted, up 94% from 400,500 jobs posted just three years earlier. In comparison, all tech job postings grew around 20% during that period. That means the demand for cloud computing and engineering talent is growing nearly five times faster than the rest of the tech industry. 

It’s no understatement to say this explosion of cloud engineering demand has created one of the biggest talent needs in the tech industry.

This gap between supply and demand has had a direct impact on the companies unable to meet their hiring needs, keeping many businesses out of the cloud. As the cloud computing industry continues to grow, competition for great cloud talent is fierce and will be for the foreseeable future.

Types of Cloud Engineer Positions

The titles cloud engineers hold vary drastically, depending on their experience, education, and the company they work at. The title of a graduate from a coding bootcamp might look different than a candidate with a four-year degree. And the role of a cloud engineer in a five-person startup will be different than at a 5,000 person company.

At the beginning of their career, a cloud engineer will start out with an entry-level role, like Cloud Engineer I or Junior AWS Engineer. New cloud engineers will typically start their careers by working on internal or external project solutions along with systems and integration testing. They can expect to work in one of these roles for one to three years.

From there, they’ll have the opportunity to move into more senior-level roles with hands-on engineering experience, such as: 

• Senior Cloud Engineer
• Cloud Engineer II
• Cloud Engineering Manager
• Cloud Security Engineer
• Senior AWS Engineer
• Systems Engineer
• Cloud Developer
• Cloud Architect
• Network Engineer

While they spend several years honing their skills, their responsibilities expand to include taking ownership of projects, working independently in a team environment, and mentoring project team members. Senior cloud engineers might also choose to specialize in a particular technology or discipline, such as cloud security or DevOps.

With some experience under their belt, a cloud engineer often faces a crossroads in their career having to choose between two paths. 

The first path is to pivot into people and team management functions. Hiring, mentoring, resource planning and allocation, strategy, and operations become a larger component of the responsibilities of cloud engineers pursuing this career path. At the higher levels of an organization, these titles include:

• Director of Cloud Networking
• Cloud Operations Manager
• Director of Solutions Architecture
• Chief Information Officer (CIO)
• Chief Technology Officer (CTO)

The second possible career path is to continue as an individual contributor. Many cloud engineers opt to continue their careers as individual contributors, enjoying equally fulfilling careers and developing deeper technical expertise in various languages and frameworks.

The motivation behind this decision is that experienced cloud engineers aren’t necessarily interested in or qualified to be managing a team. And an engineer in an individual contributor role has the opportunity to focus on growing their technical skills and learning the newest emerging technologies.

Data is scarce on how this career decision will impact long-term earning potential. Career outlook for individual contributors and managers will also depend on a number of other factors, including industry, company size, and experience.

Salary Comparisons & Job Outlook

On average, cloud engineers tend to receive a salary significantly higher than the national average in their country.

For example, in the U.S. the average salary in 2020 was $53,400. In contrast, the average base salary for cloud engineers in the U.S. is $114,323 to $130,977. That’s 114 to 145 percent more than the national average.

Junior cloud engineers can expect to occupy a lower salary band at the beginning of their careers. In contrast, senior positions provide a higher average compensation, though data for this specific salary band is hard to find. Industry and company size also affect the salary band dramatically. Historically, though, geography has had a significant impact on the compensation of technical talent — and that includes cloud engineers. 

Cloud Engineering Skills

Technical Skills

Cloud engineers use a range of technologies to build cloud-based platforms, infrastructure, and applications. 

A core requirement of cloud engineering is expertise in the technologies offered by cloud-hosting providers. These include, to name a few:

• AWS
• Azure
• GCP
• IBM Cloud
• Oracle Cloud

Recruiters and hiring managers who are hiring cloud engineers should look for in-demand competencies with the specific services and products offered by these platforms. An AWS cloud engineer, for example, might be familiar with Amazon cloud products such as Glue, Lake Formation, Redshift, Athena, MSK, and Kinesis.

Many cloud engineering roles require knowledge of data-oriented and object-oriented languages such as Java, Ruby, Python, or Clojure. Some roles also require familiarity with a general programming language, such as C, C+, C#, or Go. 

Depending on the role, software engineers might also work with a number of other tools:

• Databases (SQL, MySQL, NoSQL)
• Message brokers (RabbitMQ, ActiveMQ, Kafka)
• Big data frameworks (Apache Hadoop, Apache Spark)
• Familiarity with web services and APIs:
  • XML (Extensible Markup Language)
  • SOAP (Simple Object Access Protocol)
  • WSDL (Web Services Description Language)
  • UDDI (Universal Description, Discovery and Integration)

Some cloud engineers will specialize in DevOps, a set of practices that combines software development and IT operations. Core DevOps skills include:

• Container management software (Docker, Kubernetes)
• CI/CD tools (Gitlab, Jenkins, Nexus)
• Linux Fundamentals And Scripting
• Infrastructure as Code (IaC)

Security and Compliance

Some cloud engineers specialize in keep computing resources and data secure, operational, and compliant. Cloud cybersecurity engineers typically need an understanding of cloud cybersecurity to create cloud backup strategies in preparation for outages, natural disasters, and cyberattacks. They also need the skills to identify regulations and guidelines for compliance.

Soft Skills

Technical competency alone isn’t enough to succeed in a cloud engineering role. Mathematical, analytical, and problem-solving skills are a must in any technical role. And soft skills are even more critical in a digital-first or digital-only environment.

Employers may put even more stock into engineers with strong soft skills, such as:

• Time management
• Communication
• Project management
• Problem solving

Communication skills, in particular, are critical to cloud engineering. Cloud engineers often work in client-facing or consulting roles that require them to communicate complex information to stakeholders in other departments or companies. The ability to turn technical subject matter into easy-to-understand solutions is highly valuable to cloud engineers — and the teams that employ them.

Certifications

All of the major cloud providers offer certification courses to cloud engineers, including AWS, Azure, and GCP. In addition to providing training in the platforms, certifications also serve as a credential for cloud engineers. For roles requiring experience with cloud providers, having a certification in the appropriate platform is a mandatory or nice-to-have qualification. 

Experience & Education

After competency, the most important qualification for cloud engineers is experience. On-the-job experience and training is a critical requirement for many employers.

Then, there’s the question of education. The education requirements for cloud engineering positions vary widely. Many employers still require cloud engineering candidates to have four-year degrees. Some might even expect graduate-level degrees.

But competition for skilled cloud engineers is fierce, and it’s common for job openings requiring degrees to go unfilled. There are simply not enough engineers with degrees to fill thousands of open roles out there. Companies looking to hire cloud engineers will have access to a much larger pool of talent and achieve their cloud initiatives if they recognize other forms of education and experience. 

Resources for Hiring Cloud Engineers

Developer Hiring Solutions

How to Assess Cloud Engineering Candidates

The post What Does a Cloud Engineer Do? Job Overview & Skill Expectations appeared first on HackerRank Blog.

By 2025, the global cost of cybercrimes will reach $10.5 trillion each year, up from $6 trillion in 2020. That’s an 11.8% annual growth rate – made even more shocking by the fact that it more than doubles the global economy’s roughly 5.4% growth rate.

With cybercrimes posing such a large and growing threat, it’s no surprise that cybersecurity engineering is one of the fastest growing industries and professions in the world. The global cybersecurity market is projected to grow from $218 billion in 2021 to over $345 billion by 2026. And in 2022, Indeed ranked information security analysts thirteenth in its list of fastest growing careers of the decade.

Cybersecurity engineers are the professionals tasked with protecting the world’s applications and data from a growing list of attacks. In this post, we break down the statistics, job requirements, and responsibilities of a career in cybersecurity engineering.

What Does a Cybersecurity Engineer Do?

As long as developers have been building software, there have been bad actors trying to break into applications and engineers dedicated to stopping them.

Cybersecurity is an advancing discipline concerned with protecting and securing applications, networks, corporate data, and user data. Cybersecurity engineers are responsible for preventing, identifying, and stopping a variety of cyberattacks and breaches.

The types of attacks that cybersecurity engineers have to combat are countless, with bad actors deploying more threats regularly. The most common attacks include:

• Malware
• Phishing
• Ransomware
• Man-in-the-Middle / Machine-in-the-Middle (MITM)
• Denial-of-Service (DOS)
• Distributed Denial-of-Service (DDoS)
• Malware as a Service (MaaS)
• Cross-site scripting (XSS)
• Password attack
• SQL injection

On a more technical level, the core job responsibilities of cybersecurity engineers include:

• Responding to system and network security breaches
• Protecting the organization’s infrastructure and data
• Monitoring for new types of cyber attacks and breaches
• Working with stakeholders to secure new features
• Keeping up-to-date with advancements in technology
• Working in an agile environment

What Kinds of Companies Hire Cybersecurity Engineers?

Any company that produces software will need to hire cybersecurity engineers to protect their applications and data. With companies in every industry becoming increasingly driven by technology, the demand and opportunities for professionals with this skill set will continue to grow. The top sectors hiring for cybersecurity engineers range from small startups to Fortune 500 companies, including:

• Technology
• Finance
• Professional services
• Retail
• Media
• Manufacturing

Types of Cybersecurity Engineer Positions

The titles cybersecurity engineers hold vary drastically, depending on their experience, education, and company.

At the beginning of their career, a cybersecurity engineer typically starts with an entry-level role, like junior cybersecurity engineer or cybersecurity associate. A new cybersecurity engineer usually works in one of these roles for one to three years.

From there, they’ll have the opportunity to move into more senior-level and specialized roles with hands-on engineering experience. Cybersecurity engineering job titles include:  

• Network security engineer
• Cybersecurity technician
• Cryptographer
• White hat hacker
• Information security analyst
• Senior cybersecurity engineer

Larger companies that employ a significant number of engineers tend to use well-defined structures and pay grades for their seniority levels. For example, GitLab’s cybersecurity team uses the following title structure:

• Intermediate Security Engineer
• Senior Security Engineer
• Staff Security Engineer
• Principal Security Engineer
• Distinguished Security Engineer

While they spend several years honing their skills, their responsibilities expand to include taking ownership of projects, working independently in a team environment, and mentoring project team members.

With a few years of experience, a cybersecurity engineer often faces a crossroads in their career having to choose between a few paths. 

One path is to pivot into managing people and teams. Hiring, mentoring, resource planning and allocation, strategy, and operations become a larger component of the responsibilities of cybersecurity engineers pursuing this career path. At the higher levels of an organization, these job functions might include:

• Information security manager
• Cybersecurity engineering manager
• Director of cybersecurity
• Chief information officer (CIO)
• Chief information security officer (CISO)

Another possible career path is to continue as an individual contributor. Many cybersecurity engineers opt to continue their careers as individual contributors, enjoying equally fulfilling careers and developing deeper technical expertise in various languages and frameworks. Larger organizations might refer to individuals in these positions as individual contributor leadership to communicate the influence of their position.

An experienced cybersecurity engineer might not be interested in (or qualified) to manage a team. And engineers in an individual contributor role have the opportunity to focus on growing their technical skills and learning the newest emerging technologies.

Salary Comparisons and Job Outlook

On average, cybersecurity engineers receive highly competitive compensation packages. However, data sources on technical salaries often present vastly different – and at times conflicting – numbers at both a regional and global level. Estimates of total compensation for cybersecurity engineers in the U.S. range from $120,446 to $140,143.

Current market conditions have made technical salaries especially volatile. Because of this, public salary data may be low or out of date. Total compensation packages, including equity and bonuses, are also changing rapidly. Hiring teams need to conduct their own research to identify salary bands based on their company’s requirements and the technical needs of the role.

The job outlook for cybersecurity engineers is equally promising. As long as there are companies with software and criminals looking to break into that software, there will be a demand for cybersecurity engineers. From 2020 to 2030, The U.S. Bureau of Labor Statistics projects the number of information security professionals  in the U.S. to grow by 33 percent.

Requirements to Become a Cybersecurity Engineer

Technical Skills

Cybersecurity engineers use a range of programming languages to secure networks, databases, and applications. But a unique attribute of cybersecurity engineers is that they also have to learn the languages that attackers use to break into a company’s system. Front-end, back-end, and database languages are particularly important, as many web-based attacks happen through the systems built by these technologies. 

The languages that cybersecurity engineers use include:

• HTML
• Javascript
• SQL
• Java
• C/C++
• Python
• Ruby
• PHP

Cybersecurity engineers also use a number of tools and frameworks. The exact technologies they’ll work with depend on the role or specialization. These include: 

• Wireshark (network protocol analysis)
• Kali Linux (digital forensics and penetration testing)
• Ncat (network monitoring and management)
• SiteLock (website security and monitoring)
• John the Ripper (password cracking)
• PowerShell (task automation)
• Nmap (network scanning)
• Shell scripting

It’s worth noting that there’s a degree of fluidity to the technologies that cybersecurity engineers learn. Cybersecurity is a fast-paced discipline. Engineers in this profession need to continuously evolve and expand their skill sets to outpace the attackers trying to break into their systems.

Soft Skills

Technical competency alone isn’t enough to succeed in a cybersecurity engineering role. Mathematical, analytical, and problem-solving skills are a must in any technical role. And soft skills are even more critical in a remote-first only environment.

Employers may have a preference for cybersecurity engineers with strong soft skills, such as:

• Adaptability
• Time management
• Communication
• Project management
• Problem solving

While soft skills are important to any technical professional, communication skills are particularly important to cybersecurity. Because the majority of cyber attacks target employees, cybersecurity engineers need to have the necessary soft skills to communicate with and train both technical and non-technical stakeholders. 

Experience and Education

After competency, the most important qualification for cybersecurity engineers is experience. On-the-job experience and training is a critical requirement for many employers.

Then, there’s the question of education. 63% of cybersecurity engineers have a bachelor’s degree and 15% have a master’s degree. Many employers still require cybersecurity candidates to have four-year degrees. 

But competition for skilled cybersecurity engineers is fierce, and it’s common for job openings requiring degrees to go unfilled. There are simply not enough engineers with degrees to fill thousands of open roles out there. Companies looking to hire cybersecurity engineers will have access to a much larger pool of talent and achieve their data initiatives if they recognize other forms of education and experience. 

Resources for Cybersecurity Engineering

Developer Hiring Solutions

HackerRank Community

The post What Does a Cybersecurity Engineer Do? Job Overview and Skill Expectations appeared first on HackerRank Blog.

A software developer builds software and applications that help users perform specific functions and tasks. Software developers are also responsible for implementing larger frameworks to support specific devices or technology in a network.

In this post, we explore the skills required to be a software developer as well as career paths and its projected job outlook.

What Kinds of Companies Hire Software Developers?

Any company that’s building software or applications will need to hire software developers. The employers hiring the most engineers with this skill set are, unsurprisingly, the world’s largest technology companies, including Amazon, Accenture, InfoSys, Microsoft, and Google.

Though it’s not just Silicon Valley and startups increasing the demand for software developers. Now, more than ever, all companies are becoming tech companies. Companies in every industry need technical talent to help them modernize and innovate their business practices. Finance, social media, aerospace, defense, consulting, retail, healthcare — the demand (and opportunity) for software development talent is endless. 

Software Developer vs Software Engineer

Software development shares a lot of similarities with software engineering, and some companies even use the terms interchangeably. Developers and engineers in these roles work with similar back-end technologies. However, there are fundamental differences in the training, experience, and responsibilities of a developer and an engineer.

• Software developers are responsible for writing, managing, and maintaining software. They’re involved in the full lifecycle of software development, including research, development, testing, and launch. 
• Software engineers are responsible for the design, implementation, and maintenance of complex computer systems. Software engineers develop, design, and test software applications and apply engineering principles to the process of building software.

Types of Software Developer Positions

Software developer titles can vary widely, especially depending on their experience and the company or industry in which they work. Because the “software developer” title is broader than other technical roles, developers and employers often use different terms to describe the same role. For example, web developer and software developer are different roles that are sometimes combined into the job title web software developer.

At the beginning of their career, a software developer typically starts with an entry-level title like junior developer or software developer I. A new developer spends a lot of time learning and studying the codebases and application lifecycle of internal systems. They’re tasked with creating code models and identifying coding bugs.

After gaining several years of experience in an entry-level role, developers might have the opportunity to move into mid-level roles. At this stage, they’re responsible for developing applications from concept to launch. Depending on their specialization, experienced software developers can expect to create anything from operating systems to sophisticated proprietary software.

From there, they may have the opportunity to move into more senior-level roles with hands-on development responsibilities. Titles at this level include senior software developer, lead developer, and senior software architect. How long it takes to reach senior-level depends on the company and the skill level of the developer. 

The key requirement to reach senior-level developer roles is the ability to handle a variety of programming languages, with an exceptional command of computational logic and flow-charting. While they spend several years developing their skills, their responsibilities expand to include taking more ownership of projects, working independently in a team environment, and mentoring project team members. 

Salary Comparisons and Job Outlook

Software developers can expect to earn an average of $96,903. This estimate is based on data aggregated from leading salary data sources: 

• Payscale reports a range of $52,000 to $108,000, with an average of $$74,136
• Glassdoor reports a range of $63,000 to $147,000, with an average of $95,843
• U.S. Bureau of Labor Statistics reports a range of $64,470 to $168,570, with an average of $120,730

Software developer salaries also vary depending on specialization, with in-demand competencies commanding a higher compensation. For example, the average salary for software developers who know Clojure is $106,644. In contrast, the average for those specializing in JavaScript is $65,580.

It’s worth noting that estimates from salary aggregators may be low or out of date. While this has always been true, market conditions have made technical salaries especially volatile since 2020. Total compensation packages, including equity and bonuses, are also changing rapidly.

Requirements to Becoming a Software Developer

Technical Skills

Software developers use a range of programming languages to build software and applications. These include:

• C/C++
• C#
• Java
• JavaScript
• Python
• Ruby
• Scala
• SQL

Recruiters and hiring managers looking for software engineers should also look for in-demand competencies beyond programming languages. These include: 

• DevOps Skills
• Linux experience 
• Back-end frameworks (Ruby on Rails, Django, Laravel)
• Cloud platforms (AWS, GCP, Azure)
• Version control software (SVN, Git)
• Relational database management systems
• Non-relational database management systems

Soft Skills

Technical competence isn’t enough to succeed in software development. Analytical, mathematical, and problem-solving skills are a common part of any technical job. And in a remote or digital-first environment, soft skills are even more critical.

Employers value a number soft skills, such as:

• Communication
• Creativity
• Critical thinking
• Problem solving
• Project management
• Time management

Experience

After skill competencies, the most important qualification for software developers is experience. For many employers, “real-world” experience and training is a critical requirement.

When it comes to education, about 70 percent of developers worldwide have a bachelor’s degree or higher. If you’re recruiting, screening, or hiring engineers, it’s most likely that many of them have a degree. And many companies still require engineers to have four-year degrees.

Lately, companies looking to hire engineers are starting to recognize other forms of education and experience. Competition for skilled software engineers is high, and it’s not uncommon for job openings that require a degree to go unfilled. But employers that prioritize real-world skills over education alone gain access to a much larger talent pool.

Resources for Hiring Software Developers

• Best Practices for Hiring Software Developers: Front-End, Back-End, and Full-Stack
• How to Begin Screening Software Developers
• Developer Hiring Solutions

The post What Does a Software Developer Do? Role Overview and Skill Expectations appeared first on HackerRank Blog.