Data Engineer or Data Analyst: Which One Does Your Business Actually Need?

What Is a Data Engineer?

Data engineering covers a wide range of functions, but it essentially revolves around building and maintaining the systems that allow organizations to collect, store, and process data.

Without a solid data infrastructure, even the most advanced analytics tools won't deliver reliable, accurate insights. Data engineers help businesses by ensuring their data is accurate, accessible, and ready for analysis so decision-makers have the necessary information whenever they need it.

In such a broad field, there are different types of data engineers, including pipeline engineers who focus on moving data between systems, platform engineers who build storage and processing platforms, and many others. 

While they focus on different areas, all data engineers are expected to have key skills like database management, cloud computing, and data pipeline architecture. Soft skills, such as effective communication skills, matter too, as data engineers often work with analysts and business teams.

What Is a Data Analyst?

Being a data-driven business means making informed decisions based on facts, not just intuition. But raw data isn't useful on its own—it needs to be cleaned, analyzed, and turned into meaningful insights.

A data analyst comes in. They take complex data sets and translate them into reports, dashboards, and trends that businesses can actually use to improve operations and business strategies.

Like data engineers, there are various types of data analysts. Marketing analysts, for instance, focus on customer trends and campaign performance, while financial analysts examine revenue and expenses to improve profitability. 

No matter their focus, all data analysts should be skilled in data visualization techniques, statistical analysis, and business intelligence tools to break down data into clear and valuable insights. Hiring a competent analyst means looking for a mix of technical skills—like SQL, Python, and Excel—and soft skills like critical thinking, problem-solving, and communication for explaining findings to stakeholders.

Key Differences Between Data Engineers and Data Analysts

The role you choose depends on where your business is in its data maturity journey.

Here's a table providing an overview of the key differences between data engineers and data analysts, helping you decide which role is better suited to your data needs and goals.

How do salaries compare?

Salaries for data roles can vary widely depending on factors like skill set and experience—with location being another big one. 

When looking to save costs, hiring offshore data analysts and engineers is often a more competitive choice than hiring locally. US businesses, for instance, can tap into talent pools in nearshore regions like Latin America (LatAm), where the compensation reflects the lower cost of living there. 

To give you a better idea, here's a quick comparison of average salary ranges between US-based and nearshore hires:

If you want to dive deeper, take a look at our salary guide, which compares earnings for various data roles compared to US-based hires.

How to Decide If You Need a Data Engineer or a Data Analyst

As established, both data engineers and data analysts work with data, but they serve different purposes. A bad hire can be a costly mistake, leading to wasted time, money, and frustration.

So, how do you decide which one you need?

Here are some common cases when hiring a data engineer is ideal:

• Your data is disorganized and difficult to access: A data engineer structures raw data, making it usable by creating databases, pipelines, and warehouses.
• You’re handling large-scale automation or AI/ML: Data engineers often build and optimize infrastructure to support AI models and automation.
• Your reporting is slow due to inefficient data systems: Poorly structured databases will slow down queries and reports. A data engineer can optimize storage and retrieval.
• Your data comes from multiple sources and needs integration: If you're pulling data from different platforms (CRM, ERP, website analytics), a data engineer builds a system that connects and standardizes it.

A data engineer is crucial for businesses dealing with extensive data, needing robust infrastructure, or preparing for future-ready projects.

Alternatively, here are several scenarios when hiring a data analyst makes sense:

• You need insights to guide business decisions: A data analyst turns structured data into actionable insights through reports, dashboards, and trends.
• Your teams need help interpreting performance metrics: Data analysts break down key performance indicators (KPIs) to uncover trends in marketing, sales, and other business areas.
• Your leadership needs forecasting and trend analysis: A data analyst can predict future outcomes based on historical data.
• Your stakeholders require data visualization: A data analyst makes complex data digestible with charts, graphs, and dashboards.

You'll need a data analyst if you already have structured data and need someone to extract insights, track performance, and support data-driven decision-making.

If you need both reliable data systems and reliable insights, having both roles at hand can keep everything running smoothly. Take an e-commerce company trying to boost customer retention. A data engineer would set up pipelines to gather customer behavior data, while a data analyst would use it to find trends and reasons for drop-offs. 

Final Thoughts

Deciding between data engineer versus data analyst roles comes down to your specific data needs and business requirements. A data engineer focuses on the infrastructure and architecture that support data systems, while a data analyst turns that data into useful insights.

Both roles are crucial to creating a data-driven business, but understanding their differences helps you make the right choice and save yourself time and resources. 

At Near, we connect businesses with top LatAm talent through our comprehensive, tailored hiring solutions. Whether you need data engineers, data analysts, or both, our remote LatAm professionals bring extensive experience across industries and deliver high-quality work.

Want to learn more about hiring a data engineer? Check out our article “How to Hire a Remote Data Engineer: Steps and Best Practices.“ Or, if you're looking to enhance your data analytics, take a look at “Need to Hire a Data Analyst? Here’s Everything You Need to Know.”