DevOps vs. Data Engineering: Which One Should You Hire?

If you aren’t a techie yourself, hiring tech talent can feel like ordering from a menu written in another language, especially when choosing between a DevOps vs. data engineer. While both roles sound equally technical (and a bit mysterious), confusing them can lead to costly missteps and lost productivity. 

Knowing the difference doesn’t just help you hire smarter but also keeps projects running smoothly and budgets in check. 

In this article, we’ll break down exactly what DevOps engineers and data engineers do, highlight their key differences, and help you understand when you might need one (or both) on your team. 

What Is DevOps, and What Do DevOps Engineers Do?

Since the term “DevOps” was coined in 2009, it’s become one of those tech buzzwords you hear often. But what does it actually mean? 

At its core, DevOps (development operations) breaks down the barriers between software developers and IT operations teams. Think of it kind of like tech therapy, helping both sides communicate clearly and collaborate effectively, so that software gets delivered faster and with fewer issues.

DevOps engineers play a pivotal role in making this happen. Their responsibilities usually center around three main areas:

• Infrastructure automation: They create automated workflows to deploy servers, manage networks, and scale applications effortlessly.
• Continuous Integration/Continuous Delivery (CI/CD): DevOps engineers set up systems to automatically build, test, and deploy software, reducing human error, speeding up software releases, and boosting overall productivity.
• Cloud infrastructure management: DevOps engineers handle the nuts and bolts of cloud setups, including scalability, security, and performance optimization.

What Is Data Engineering, and What Do Data Engineers Do?

If DevOps engineers keep your apps running smoothly, data engineers are the ones who make sure your company’s data doesn’t turn into digital chaos. Data engineering involves designing and managing systems that collect, store, and process large amounts of data. This makes it easier to access, analyze, and actually use data to grow your business.

Data engineers handle several key responsibilities:

• Building and maintaining data pipelines: Data engineers set up efficient systems that transfer data from multiple sources to one centralized location, meaning it stays organized and ready for analysis.
• Extract, Transform, Load (ETL) processes: Unfortunately, data rarely arrives neat and tidy. ETL processes clean it up by extracting data from various sources, transforming it into consistent formats, and loading it into databases or data warehouses for easy access.
• Database management and optimization: Data engineers make sure that your databases are optimized for speed, scalability, and reliability. Good database management means faster reports, quicker insights, and fewer late-night panics about downtime.

Since data engineering covers multiple specialties, it’s worth exploring the different types of data engineers to figure out which fits your business best. Hiring the right one means clearer data-driven insights and better data quality for your data-driven decisions.

Key Differences Between DevOps and Data Engineering

Both DevOps and data engineering involve technical skills, problem-solving, and keeping systems running. But they have distinct objectives, workflows, and areas of expertise. 

Confusing the two can lead to hiring someone who doesn’t match your company’s actual needs.

Here’s how the roles differ in some key areas:

• Tech stack: DevOps engineers primarily focus on cloud services, infrastructure automation, and tools designed for software deployment. On the other hand, data engineers concentrate on technologies built around data storage, ETL processes, and database systems.
• Workflows: DevOps workflows revolve around rapid deployment and continuous improvement of software applications. Their goal is quick releases, reduced downtime, and streamlined collaboration between development and IT teams. 

Data engineering workflows are oriented around the reliability, accuracy, and efficiency of data pipelines. Their processes guarantee data integrity, consistency, and ease of analysis, helping data teams provide accurate insights faster.

• Collaboration: DevOps engineers collaborate closely with software developers, QA teams, and operations, meaning the development cycle runs smoothly and efficiently. Meanwhile, data engineers primarily interact with data scientists, analysts, and business stakeholders who depend on clean, accessible data to inform strategic decisions.

When Should You Hire a DevOps Engineer vs. a Data Engineer?

The key to choosing between a DevOps engineer and a data engineer lies in clearly defining your business goals. 

Ask yourself: What specific problem are we trying to solve? Understanding your company’s current and future technical needs makes hiring decisions straightforward and prevents wasting resources on roles that won’t directly support your objectives.

Here’s a simple breakdown of when each role is typically most beneficial.

When to hire a DevOps engineer

If your primary goals include faster software deployments, reliable infrastructure, and the ability to scale quickly, a DevOps engineer should be your first choice.

For example, if your business regularly rolls out new features, faces downtime due to deployment issues, or struggles to manage cloud resources effectively, a DevOps expert can dramatically improve your workflow and productivity.

When to hire a data engineer

If your company relies heavily on data-driven decisions, faces challenges in managing and accessing data efficiently, or needs accurate, timely data for advanced analytics, it’s time to bring in a data engineer. 

Companies that employ data scientists or analysts and deal with large-scale analytics or machine learning projects greatly benefit from dedicated data engineering support.

When you need both 

In reality, many businesses find themselves needing both roles simultaneously. If your organization develops complex software products and also relies heavily on data analytics, hiring both DevOps and data engineers becomes essential to providing a smooth deployment, scalability, and reliable data management.

Also, remember that hiring a data engineer is not always straightforward. If you’re unsure whether you specifically need a data engineer or another data specialist like a data warehouse architect, clarify this distinction early, as it will save time, effort, and expenses later.

Can One Person Cover Both Roles? 

You might wonder: could one talented engineer handle both DevOps and data engineering? While the idea is tempting (and sometimes possible), hybrid roles come with distinct advantages and drawbacks.

On the plus side, hiring someone who can do both can be budget-friendly, especially for smaller startups or early-stage companies. It gives you broader technical coverage without the expense of two separate hires. For businesses just getting started, one multi-skilled engineer can be a practical, economical solution.

However, there are important downsides to consider. Asking one person to cover two complex roles often leads to burnout. Both fields require specialized knowledge, making it challenging for a single individual to maintain deep expertise in both areas simultaneously. 

Additionally, finding someone genuinely skilled in both DevOps and data engineering is tough as, typically, they’ll excel in one and have only a surface-level skill set in the other. 

How to Find Qualified DevOps or Data Engineers for Your Business 

Once you’ve decided whether you need a DevOps or data engineer (or both), the next step is finding skilled candidates who match your requirements. Luckily, there are several practical options to help you locate the right talent:

• Professional job boards: Platforms like LinkedIn or Indeed are ideal for finding qualified professionals who are actively seeking long-term roles.
• Freelancer platforms: Websites like Upwork or Fiverr can connect you quickly with DevOps or data engineering freelancers, perfect for short-term or project-based needs.
• Specialized offshore hiring companies: If you’re open to international talent, consider recruitment partners who specialize in helping businesses hire DevOps or data engineers from outside the US. They handle candidate screening and international compliance and payroll, simplifying the process of hiring offshore so you can benefit from the lower salary expectations in areas of the world where living costs are lower than in the US.
• Recruitment and staffing agencies: For both local and international DevOps and data engineering talent, staffing or recruitment agencies typically have talent ready to start immediately or can source talent quickly. They work with your business and, like remote hiring partners, simplify the onboarding process.
• Personal referrals: Your own professional network can be invaluable. Trusted contacts often recommend talented engineers who perfectly match your company’s culture and requirements.

Before you begin interviewing candidates, take a quick look at the top skills for data engineers and DevOps specialists so you know exactly what to look for.

Final Thoughts

Choosing correctly between DevOps and data engineering boils down to clearly understanding your business priorities. DevOps engineers accelerate software delivery and provide reliable infrastructure, while data engineers manage and optimize your data pipelines for better analytics and insights. 

One similarity between the two isn’t actually technical, but in recruitment. Given the high demand in both areas, hiring can get competitive. 

North America is currently the largest region in the DevOps market, intensifying competition for skilled engineers. At the same time, the demand for data engineers is outpacing the average job growth in the US, meaning these specialists are equally tough to recruit.

Businesses can turn to nearshoring—a type of offshoring—to Latin American countries to help fill the skills gap. This approach comes with significant cost savings, with average annual salaries for data engineers from LatAm coming in at an average of 52% below US-based hires. DevOps talent is also comparable, with a 54% saving when compared to US-based average salaries.

At Near, we simplify the hiring process by connecting you with top remote data engineering talent or DevOps engineers from LatAm quickly and effectively. 

Want to learn more about hiring data engineers from Latin America? Check out our article, “Why You Should Hire Nearshore Data Engineers and How to Do It.”