Data Engineer vs Software Engineer: Key Differences and Similarities

What comes to mind when you think about building a website or mobile application? Probably writing code. Software developers create the front-end interfaces and back-end infrastructure of the computer programs we use day-to-day. However, many of these functionalities are built and maintained by data engineers — particularly applications handling large volumes of data with complex API calls. Data engineers operate behind the scenes, building databases, data warehouses, and data pipelines to make the organization’s data usable for data scientists and business analysts. 

While the data engineering and software engineering professions are often confused, each role has distinct responsibilities, skills, and education requirements. Keep reading to deep dive into the differences and similarities of data engineers and software engineers. 

Data engineers design, build, and maintain IT infrastructure for handling big data efficiently. Enterprise software programs like ERP systems, fintech platforms, or inventory management tools generate and serve content based on user interactions or data inputs. They require a robust data architecture to access, store, process, and analyze data. 

For example, an ecommerce platform lets users make purchases, update account information, and view the product catalog. Data engineers build data pipelines that enable the organization to analyze huge volumes of transactional data and create a more personalized purchase experience through marketing campaigns, recommendation engines, and dynamic content. They build data models to organize and structure data, integrate data from disparate sources — including databases, APIs, and files — and optimize storage systems.  

Software engineers design, develop, test, and maintain software applications. They are responsible for the entire software development life cycle, from gathering requirements to deployment and maintenance. Some developers specialize in front-end development (user interfaces, animations, and dynamic content) or back-end development (server-side programming, API development, and security). Full-stack developers do both. Engineers work in teams to code different components of a software system. They also run code reviews, document their code, and debug software. 

In an industry fraught with buzzy new job titles — eg: chief innovation evangelist at Google —  folks often misunderstand the difference between ‘data engineer’ and ‘software engineer.’ Both roles require transferable programming skills like data structures and algorithms, application development, and problem-solving, but each one oversees a different aspect of software development. 

Here’s a comparison of data engineering vs. software engineering:

While both fields overlap, data engineering and software engineering entail different skill sets, responsibilities, and outputs.

A bachelor’s degree in computer science, IT, or a related field may help you get your foot in the door, but alternative credentials impart job-focused skills in less time at a far lower cost. Examples include IT certifications, online courses, or bootcamps. While the tech industry has a reputation for favoring practical experience over degrees, both professions require a strong foundation in computer science principles. 

On top of that, data engineers need specialized programming skills like database management, AI and machine learning, data warehousing, data modeling, or data science. Aspiring professionals can gain these skills through online courses, internships, and hands-on projects.

Although I don’t have a tech background outside of this bootcamp, I can make up for my weaknesses through lots of practice and study, and by taking advantage of all the bootcamp has to offer. I now know how to build a website from scratch. Samuel Luo, TripleTen Software Engineering program student. 

The top data engineering skills

Data engineers must be fluent in Python, SQL, Java, or Scala — the most common programming languages used for data processing. They’re expected to write efficient code to extract, transform, and load (ETL) data from various sources and understand how to use relational databases (eg: PostgreSQL, MySQL) to store and manage data.

Here are some key data engineering tools you need to know:

• Libraries and frameworks for data manipulation, including Pandas, Matplotlib, and Scikit-Learn.
• Cloud computing platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) are essential for deploying and managing data infrastructure in the cloud. 
• Big data technologies such as Hadoop, Spark, and Kafka are valuable for real-time or batch-processing big data. 

The modern world takes place around data — big data, small data. It’s always about data. Evgeniia Unzhakova, a graduate of TripleTen’s Data Science program and a research analyst at the University of North Carolina at Chapel Hill. 

The top software engineering skills

Software engineers should aim to master at least one programming language — depending on their preferred computing platform or operating system. Python is the second most used programming language on GitHub, renowned for its versatility.  

• Prospective developers should know the software development life cycle (SDLC) inside out, from gathering requirements to deployment.
• Be familiar with mainstream methodologies like Waterfall, DevOps, and Agile. 
• Proficiency in version control systems such as Git helps programmers manage source code, track changes, and collaborate with fellow devs. 
• Some AI-forward employers expect developers to have experience using AI copilots to write more efficient code. 

Finally, developers need to know software testing frameworks and automation scripts to ensure software meets business requirements. 

While software engineers focus on the user-facing aspects of software applications, data engineers help organizations connect disparate data sources for a fully integrated tech stack. 

Top data engineer responsibilities

• Gathering requirements - Data engineers work with stakeholders to understand data requirements, including data sources, formats (structured vs. unstructured), quality (accuracy, completeness, relevance), and usage.
• Data architecture design - Design and implement data architectures to store, analyze, and process large volumes of data efficiently.
• Data modeling - Develop conceptual models to show the entities, attributes, and relationships within the organization’s data. This helps organize and structure the data for storage, retrieval, and data analysis. 
• ETL (Extract, Transform, Load) Development - Design and maintain ETL processes to extract data from various sources, transform it into a usable format, and load it into data storage systems.
• Data pipeline development - Build and maintain data pipelines to automate the flow of data between systems, processes, and applications.
• Data management - Manage database systems and storage solutions, including relational databases, NoSQL databases, data lakes, and data warehouses.
• Cloud computing - Deploy and manage data infrastructure in AWS, Microsoft Azure, or GCP.

Data engineers work across numerous industries that handle big data, including healthcare, retail, telecommunications, and more.

1. Ecommerce platforms - E-retailers like Amazon, Walmart, and eBay collect vast amounts of data on customer behavior, product inventory, sales transactions, and website interactions. Data engineers help organizations manage and process this data. They build data pipelines to ingest and transform transactional data, design databases to store product information, and fully integrate the organization’s tech stack (eg: CRM tools, payment gateways, POS systems).  
2. Social media network - Sites like Facebook, Instagram, and TikTok handle enormous volumes of user data, including uploaded content, engagement metrics, and advertising data. Data engineers optimize data infrastructure for fast retrieval of user-generated content. 
3. Financial trading platforms - Robinhood, Fidelity, and other trading platforms rely on real-time data feeds from stock exchanges and market data providers. Data engineers build low-latency data pipelines to process streaming market data and design databases to store historical trading data for backtesting and analysis. 

Top software engineer responsibilities

• Gathering requirements - Collaborate with clients, users, and product managers to define project requirements. 
• Software design - Design the architecture, components, and modules of software systems to meet business and user requirements.
• Programming - Write clean, maintainable, and efficient code in one or more programming languages, such as Java, Python, or C++.
• Testing - Develop and execute test plans, test cases, and automated tests to ensure the quality and reliability of software applications.
• Deployment - Push code to production, communicate rollout plans, perform thorough testing and validation. 
• Maintenance - Provide ongoing support for deployed software applications, including monitoring performance, troubleshooting issues, and applying updates and security patches.

Software engineers can snag employment in virtually any industry as intense competition pushes businesses to become more digitally mature. 

1. Web applications - These software programs run on web servers and are accessed via web browsers. Examples include ecommerce websites, online banking platforms, and productivity tools like Google Docs. Software engineers design, develop, test, and maintain the software architecture, user interface, and backend logic of web applications. 
2. Mobile applications - Mobile apps are optimized for smartphones and tablets. Mobile games, social networking apps, productivity apps, and navigation tools like Google Maps are examples. Software engineers develop mobile applications using platforms and frameworks such as iOS (using Swift or Objective-C) and Android (using Java or Kotlin), ensuring compatibility, performance, and user experience across devices and operating systems.
3. Desktop applications - These applications are installed and run directly on PCs. Examples include office productivity suites like Microsoft Office, graphic design software like Adobe Photoshop, and media players like VLC Media Player. Software engineers use programming languages and frameworks appropriate for the target platform (eg: Windows, macOS, or Linux), ensuring functionality, usability, and performance.
4. Embedded systems - These specialized computer systems perform specific functions within a device. For example, IoT (Internet of Things) devices predict machine failure in manufacturing plants. Software engineers develop embedded software using programming languages like C or C++, optimizing code for resource-constrained environments and ensuring reliability and real-time performance.

Both data engineering and software engineering are high-earning professions_{The Entry-Level Software Engineering Salaries Bootcamp Grads Earn} with growing demand. According to Glassdoor, software engineers in the U.S. earn an average annual salary of $143,000 for all years of experience, while data engineers take home $153,000 per year. Like any field, earning potential varies with location, job title, area of expertise, and experience. 

Entry-level salary for data engineer and software engineer by state

The table below lists average earnings for entry-level_{Getting an Entry-Level Tech Job With No Experience: Why You’re an Asset} data engineers and software engineers, respectively, in the top 10 U.S. states for tech professionals_{The Top 10 States for Tech Professionals}. Salaries reflect averages for those with 0-1 years of experience.

Demand for data engineers and software engineers is growing, thanks to the explosion of big data generated by emerging technologies, including IoT devices, generative AI, blockchain, robotics, and mobile payments. Organizations hire tech professionals to leverage raw data, helping the business gain a competitive edge and make informed decisions. 

Zippia, a popular job board, predicted a 21% growth rate in data engineering jobs from 2018-2028. Meanwhile, demand for software engineers is similarly strong — the U.S. Bureau of Labor Statistics projected the developer job market will expand 25% from 2022-2032. 

If you’re considering a career as a data engineer or a software engineer, the data shows you can expect a high starting salary, opportunities for promotions along a technical or managerial path, and a strong demand for your skills across a range of industries. Demand for workers in the tech sector is expected to remain strong in 2024, with industries like education, financial services, healthcare, and manufacturing hiring the most, according to a report by recruiting firm Robert Half.

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