Benefits of Hiring a Data Engineer: Why Your Growing Business Might Need One

Computer scientist Daniel Moran once said, “You can have data without information, but you cannot have information without data.” It’s a clever way of pointing out a common problem: Many growing businesses are swimming in data but can’t do much with it. 

Reports take days, and numbers don’t line up. Key insights get lost in the noise. The good news, however, is that hiring a data engineer can help turn all those ones and zeros into usable and actionable data.

This article will go over the benefits of hiring a data engineer, how they can make your operations more efficient, and why hiring from regions like Latin America is making top-tier data talent realistic for companies of all sizes—not just those with deep pockets.

What a Data Engineer Actually Does (And Why It Matters)

A data engineer turns messy, scattered information into something your team can actually use. They build and maintain the systems that collect, clean, and organize data so it flows where it needs to quickly and reliably. Think of them as the behind-the-scenes builders who set up the roads and bridges your data travels on.

It’s a common mix-up, but data engineers aren’t the same as data analysts or data scientists. Analysts interpret trends. Scientists build predictive models. Engineers make sure the data is structured and accessible in the first place so everyone else can do their job properly.

Their day-to-day tasks typically include:

• Designing and maintaining databases
• Building ETL pipelines (Extract, Transform, Load)
• Automating manual data processes
• Enabling real-time reporting and analytics

Strong data engineers are fluent in multiple programming languages, understand cloud architecture, and know how to work across tools like Spark, SQL, and Airflow. Besides these technical skills, they’re skilled problem-solvers who think in systems, not just scripts.

When your business starts relying on data to make decisions, having the right person to build that foundation can make everything run smoother and faster across the board.

Top Benefits of Hiring a Data Engineer 

Hiring a data engineer is, in a way, about wrangling numbers. It’s also about unlocking smarter, faster growth. For businesses looking to scale without adding more complexity, a data engineer can provide the systems, automation, and accuracy that support confident decision-making and cross-team alignment. 

Below, we’ve listed five ways they can help your business make better use of its data.

1. Build better systems for your data

Many companies still rely on patchy spreadsheets and disconnected tools to manage business data. It’s quick and familiar, but it really doesn’t scale. This kind of setup often leads to data silos, inconsistencies, and long delays in reporting. In fact, according to research by IBM, 82% of enterprises say data silos disrupt their workflows.

A data engineer helps fix this by building structured pipelines and centralized databases. These systems consolidate your data across platforms and tools, giving your team a single source of truth. 

That means fewer conflicting reports, faster access to up-to-date metrics, and more time spent acting on insights instead of chasing them down.

2. Free up your team’s time

Manual reporting. Copying and pasting between spreadsheets. Constant data cleanup. These tasks quietly drain your team’s time every week. According to one study, 59% of workers say they could save six or more hours weekly if repetitive tasks were automated. Most would use that time for strategic work.

A skilled data engineer builds automation into your data workflows. From daily reports that update themselves to dashboards that pull in real-time insights, they eliminate busywork so your team can focus on decisions, not data entry.

3. Fuel faster, better decision-making

Speed matters when your business is growing. But speed without accuracy can be risky. A data engineer helps you strike the right balance by making sure your data is clean, reliable, and instantly accessible. That allows leaders to make informed decisions quickly without having to second-guess the numbers.

A Forrester Consulting report (commissioned by AWS) found that data integration efforts deliver a 33% return on investment and directly support better-informed decisions. When the right data flows to the right people at the right time, decisions stop feeling like guesses and start driving results.

4. Improve operational efficiency

Data workflows go beyond mere analytics. They also power everything from marketing dashboards to sales reports and inventory tracking. A data engineer builds systems that connect these departments, cutting down on manual handoffs and duplicate work.

When every department pulls from the same live data, reporting becomes faster and more accurate. 

There’s less back-and-forth between teams, fewer errors to clean up, and more confidence in the numbers being shared. Centralized data systems also reduce the friction that comes with siloed tools. This way, marketing, sales, and operations can work off the same page instead of chasing different versions of the truth.

5. Future-proof your business

The best time to build a solid data foundation is before you need it. AI, machine learning, and predictive analytics are no longer just for giant corporations. They are quickly becoming standard tools for businesses that want to stay competitive. These technologies rely on clean, structured, and scalable data.

A data engineer helps make sure that your infrastructure is ready to support future needs. Cloud-based data systems are now essential for AI and advanced analytics. If you build the right architecture today, you avoid having to retrofit outdated systems later.

Future-proofing also means thinking beyond technology. As your data strategy evolves, consider the different types of data engineers your business might need. That could include big data specialists or engineers focused on Azure and cloud environments.

Hiring a Data Engineer From the US Isn’t Your Only Option (Or Your Best One)

For many growing companies, hiring a data engineer in the US feels out of reach. There’s a clear reason for that. 

As demand increases for structured data to support AI, analytics, and business intelligence, data engineering roles have become some of the most expensive to fill. According to our own research on US and offshore salaries, data engineers in the US typically earn between $87,000 and $177,000 per year. 

In high-cost tech hubs such as San Francisco, it’s not uncommon to see salaries reaching upwards of $400,000 for experienced professionals.

These numbers are often unrealistic for startups and mid-sized businesses. The good news is that you don’t have to hire locally to find top-quality talent. Data engineering is a role that can be done entirely remotely, which means you can access top talent from anywhere in the world. By turning to the right offshore regions, you can access highly skilled remote data engineers at a much more manageable cost.

For example, our salary data shows that data engineers in Latin America earn between $42,000 and $84,000 per year. That represents an average savings of 52% compared to US counterparts. This gap reflects the difference in cost of living and salary expectations, not a difference in ability or qualifications.

Businesses that want to hire remotely have several paths to explore. Partnering with a recruitment agency that specializes in offshore or nearshore hiring can help you connect with vetted professionals quickly. It removes a lot of the guesswork and speeds up the hiring process. 

Some companies also consider hiring a freelancer instead of a full-time team member. That approach can work in certain cases, although it often comes with challenges around availability, long-term commitment, and data security.

Why Latin America makes sense for growing companies

Hiring from Latin America offers more than just lower salaries. It also brings several practical advantages that make collaboration easy and effective:

• Time zone alignment: LatAm countries share or closely match US time zones, making real-time communication easy.
• Technical depth: The region has a fast-growing, well-educated talent pool of engineers with strong data and cloud experience.
• Cultural fit: Many LatAm professionals have worked with US-based teams before and bring a high level of English proficiency.
• Cost efficiency: Lower living costs translate to more accessible salary expectations without sacrificing expertise.

These advantages make it easier for companies to hire strong engineers who can build reliable data infrastructure and support data-driven decision-making, without blowing through limited budgets.

Thinking beyond local hiring gives you access to global talent that makes your business smarter, faster, and more competitive.

Final Thoughts

Data is one of your biggest competitive advantages, but trying to manage it manually will only get you so far. As your business grows, so does the complexity of your data. Without the right systems in place, that complexity can slow you down.

Hiring a data engineer is no longer a luxury reserved for massive tech companies. It’s a smart, realistic move for mid-sized businesses and startups that want to scale efficiently. And it doesn’t require a Fortune 500 budget. Hiring from a nearshore market like Latin America can help you build a strong data foundation without overspending.

That’s exactly where Near can help. We connect businesses with top-tier data engineers across Latin America, making it easier to hire experienced professionals who align with your time zone, your budget, and your long-term goals.

To dive deeper into hiring from Latin America, read our article on why you should hire nearshore data engineers and how to do it.