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Key Takeaways
- A data engineer builds and maintains the infrastructure and pipelines that organize raw data, making it accessible for analysis by data scientists, analysts, and business teams.
- A software engineer designs, develops, and maintains software and systems to improve functionality, user experience, and overall performance.
- You’ll want to hire a data engineer when your company is looking for someone to expertly manage your data needs and a software engineer when you want to build or enhance software solutions, apps, or digital platforms.
Your business is scaling, and you’re planning to launch a platform that collects user data to offer personalized recommendations.
But as you start to outline what you want to accomplish, confusion kicks in. While software engineers and data engineers both work with technology and code, they focus on very different aspects of the process, so their job responsibilities differ significantly. Which specialist do you need?
In this article, we'll look at the differences between data engineers and software engineers as well as factors to help you decide which one your engineering project actually needs.
Data Engineer vs. Software Engineer: What Is the Difference?
It's easy to see why data engineers and software engineers might seem similar. Both engineering roles involve coding, working on complex systems, and contributing to a company's digital success.
To help clarify, here's a rundown comparing their key differences:
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Data scientists, analysts, business intelligence teams, internal teams like finance, or operations
General public, clients, internal teams who use the software solutions built in-house
Now that you've seen these biggest differences at a glance, let’s take a deeper look at each role.
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Data engineers
Your company data is a goldmine, but poor data quality can block growth, lead to bad decisions, and cost you valuable time and money.
Data engineers are the backbone of any analytics operation. Their job is to design and maintain the systems that move data across your organization and turn raw inputs into structured, accessible datasets ready for analysis.
They work with ETL (extract, transform, load) pipelines, integrating data from various sources such as APIs, databases, and third-party apps and preparing it for use in reporting tools and machine learning models. This involves writing complex SQL queries, scripting with Python, and using cloud-native tools like Azure Data Factory, AWS Glue, or GCP Dataflow, depending on the platform.
There are many types of data engineers specializing in areas like data architecture, real-time processing, or data quality engineering. Regardless of their specialization, a strong foundation in big data technologies (such as Spark, Kafka, Hadoop) and data warehousing solutions (like Snowflake or Amazon Redshift) is essential.
While technical expertise is important, soft skills are equally valuable in engineering. The most effective engineers can collaborate with analysts, product managers, and other engineers to understand data needs and build scalable infrastructure accordingly.
Data engineers often work remotely, so freelance data engineers can be brought on for specific short-term projects like building new, efficient pipelines or migrating legacy systems. And if you're looking for collaboration with engineers in similar time zones, nearshore data engineers (professionals from nearby countries) offer technical alignment without logistical barriers.
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Software engineers
Software engineers are responsible for building the applications, platforms, and internal tools that power digital products and business operations. Their work spans everything from writing back-end services that handle complex business logic to designing intuitive front-end interfaces for end users.
There are several software engineering roles to consider: front-end, back-end, full-stack, DevOps, mobile, plus a few more niche modalities. Each plays a part in turning a product vision into functioning software.
Back-end engineers typically work with languages like Java, Python, or Node.js to design, build, and maintain the server-side of web applications, while front-end engineers rely on React, Angular, or Vue to craft responsive user interfaces (UI) for websites and web applications.
Full-stack developers combine both skill sets, often managing entire features from database to UI. Across the board, version control systems like Git, CI/CD tools such as Jenkins and GitHub Actions, and cloud infrastructure knowledge (AWS, Azure, GCP) are critical parts of the workflow.
As with data engineers, many software engineers work effectively in remote setups. Offshoring and nearshoring (outsourcing work to professionals in nearby countries) are common practices for companies looking to scale efficiently without sacrificing quality.
How do salaries compare?
Salary expectations differ across engineering roles, but location is one of the biggest factors affecting what you’ll pay. On average, data engineers earn more than software engineers, largely due to the complexity of building and managing data infrastructure.
That said, both roles can be filled by highly skilled nearshore talent, such as engineers from Latin America (LatAm), at a significantly lower cost than US-based hires.
Here’s a quick look at average base salary ranges:
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If you're hiring a data engineer, you can use our Data Roles Salary Guide to compare earnings across multiple roles. For software-focused positions, explore the IT Roles Salary Guide to get a sense of typical compensation benchmarks.
How to Know Which One to Hire: Data Engineer or Software Engineer?
While we've defined each engineering role, a skills mismatch can still occur, leading to wasted resources, stalled projects, and frustration on both sides—something every business wants to avoid.
To guide your decision, here are some ways to determine which engineering role to hire.
These are some common cases when hiring a data engineer might be the best move for your business:
- Your data is disorganized and hard to manage: A data engineer can design and implement systems and processes to make data collection and organization more accessible and efficient.
- Your data somehow leads to inaccurate reporting: Data engineers implement tools to filter and validate data to make sure that your business intelligence is based on trustworthy information.
- Your team can't access real-time data: Data engineers create infrastructure that allows seamless data access, empowering analysts and decision-makers with up-to-date insights.
- Your business is scaling and your data volumes are increasing rapidly: A data engineer can optimize your data systems to handle larger volumes, preventing bottlenecks and improving system performance.
A data engineer is ideal if your business relies heavily on data and needs someone to create, maintain, and optimize the data infrastructure.
On the other hand, here are some instances where hiring a software engineer might be the right call:
- You need to build or improve a software product, like a mobile app or website: A software engineer can design and code the features your users will interact with.
- Your current systems need integration or custom APIs: Software engineers can help connect various applications to streamline your processes.
- Your platform or app needs bug fixes or performance improvements: A software engineer can troubleshoot issues, optimize the code, and enhance the user experience.
- You want to automate repetitive business processes: A software engineer can build software solutions to save time and increase operational efficiency.
A software engineer is a great fit if your focus is on building, maintaining, or scaling digital products and software solutions.
Because data engineers and software engineers share some overlapping skills like programming and system design, they can sometimes transition between each role.
However, the key thing to remember is that data engineers focus on specialized data tasks such as database management, while software engineers handle broader software applications. Separating these roles allows each professional to focus on what they do best, leading to better results in both areas for your business.
Final Thoughts
If managing, organizing, or scaling data is a challenge, a data engineer can streamline your pipelines and improve data accuracy. Meanwhile, a software engineer is better suited to building software, enhancing user experience, and optimizing systems.
Want to learn more? If you think a data engineer is the right choice, check out our article “How to Hire a Remote Data Engineer: Steps and Best Practices“ for expert guidance on finding the right remote talent.
Or, if software development is more your focus and you need a software engineer, explore our article “Discover the 22 Best Countries to Hire Remote Software Engineers and Developers“ to figure out where to look.
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