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Business Intelligence Engineer vs. Data Engineer

BI Engineer vs. Data Engineer: What’s the Difference and Who Should You Hire?

What’s the difference between business intelligence vs. data engineering, and who should you hire first? Here’s how to make the right call.

BI Engineer vs. Data Engineer: What’s the Difference and Who Should You Hire?

Outline

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9
 MINUTE READ
What Does a BI Engineer Do?
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What Does a Data Engineer Do?
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BI Engineer vs. Data Engineer: A Side-by-Side Comparison
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When Should You Hire a BI Engineer vs. a Data Engineer?
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Key Skills to Look for in BI and Data Engineers
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Final Thoughts
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Key Takeaways

  1. BI engineers turn structured data into actionable insights, while data engineers build the infrastructure that collects, stores, and prepares raw data for use. Both roles are essential, but they solve different problems.
  2. Hire a data engineer when you’re building data infrastructure or need ETL pipelines, and hire a BI engineer when your data is organized but lacks clear reporting or detailed insights.
  3. Most growing businesses eventually need both roles working together. While hiring both in the US can be costly, finding remote talent in Latin America makes building a complete data team accessible for most growing companies.

So, your business (like so many others) is probably sitting on a mountain of data. The challenge is that it’s not much use unless you can organize it, understand it, and actually use it to make smarter data-driven decisions.

That’s why BI and data engineers are required to make sense of it all.

But here’s the tricky part: when it comes to business intelligence vs. data engineering, asking which one you need is a bit like asking if you need a map or a road. The truth is you likely need both.

In this article, we’ll look at what each role actually does, how they impact business growth, when to hire them, and the key skills to look for so you can build a data team that delivers.

What Does a BI Engineer Do?

Companies rely on business intelligence to guide both daily operations and long-term planning.

Business intelligence engineers take structured data and turn it into something your team can actually work with. They typically work closely with stakeholders to understand what kind of data-driven insights the business needs. From there, they design the data pipelines, manage warehouses, and structure information in a way that allows teams to access and interpret it easily.

The goal is to help people make smarter business decisions using clean, organized data. Whether it’s tracking performance, identifying trends, or surfacing new opportunities, a strong BI engineer lays the foundation that makes those insights possible.

A common question is whether a BI engineer and a BI developer are the same. The answer is no. A BI engineer builds the backend infrastructure and prepares the data, while a BI developer uses that infrastructure to create the BI solution.

This includes working with data sources, warehouses, and models to create dashboards and reports. In smaller teams, one person may take on both roles (often called a full-stack BI engineer) but in larger orgs, the BI engineer supports the BI developer by feeding them well-prepped data.

What Does a Data Engineer Do?

Poor data quality costs businesses nearly $13 million a year. It’s no surprise, then, that skilled data engineers are in high demand. It’s also the reason why these professionals command six-figure salaries.

Data engineering is all about building and maintaining the systems that move, store, and clean data. These engineers design pipelines that take raw information from various sources and transform it into a usable format. Without them, your BI dashboards, data science models, and reports wouldn’t have anything accurate or useful to run on.

Their work is foundational. Without solid data pipelines, business intelligence tools, analytics dashboards, and predictive models don’t have reliable information from which to draw.

There are several types of data engineers, depending on the needs of the company. These include warehouse engineers, who manage cloud storage and data architecture and platform engineers, who develop internal tools for data teams to work more efficiently.

Some people refer to BI engineers as a type of data engineer, but they’re focused on different parts of the process. Let’s look at how the two compare.

Laptop screen showing business intelligence dashboard analytics

BI Engineer vs. Data Engineer: A Side-by-Side Comparison

Understanding the distinctions between BI engineers and data engineers will help you build an effective data team. 

Below is a comparison at a glance:

Comparison chart of BI engineer vs data engineer roles

Common misconceptions about these distinct roles

Even with a clear side-by-side comparison, it’s easy to mix up the responsibilities of BI engineers and data engineers. Since their work is so closely connected, they are often confused or misrepresented in job descriptions.

Here are two of the most common misconceptions that tend to cause confusion:

  • “BI engineers don’t code.” – This one comes up a lot, but it’s not true. While they may not be writing complex backend systems, BI engineers often write advanced SQL queries and use scripting languages like Python to automate data transformations or connect to APIs. Coding is a core part of the job, but it just looks different from what a data engineer does.
  • “Data engineers handle all analytics.” – Data engineers make sure the data is collected, stored, and available. But they don’t typically analyze it or turn it into visual insights. That part falls to BI engineers and data analysts, who know how to interpret the data in ways that align with business goals.

Clearing up these assumptions can help you avoid hiring someone for the wrong role or expecting the right person to do the wrong job.

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

Knowing who and when to hire can save your team time, budget, and a whole lot of confusion. While both roles are essential for a strong data operation, they solve different problems at different stages of growth.

When to hire a data engineer

If you’re just starting to collect and centralize your data, a data engineer should come first. You’ll need one if:

  • You’re building out infrastructure from scratch
  • You want to set up a data lake or warehouse
  • You need reliable ETL pipelines to move data between systems

For example, a SaaS company launching its first product may need to connect user activity logs to a reporting database. An e-commerce brand scaling across regions may need better data pipelines to unify inventory, sales, and customer behavior. In both cases, a data engineer makes that possible.

When to hire a BI engineer

Once your data is structured and stored, a BI engineer can help make sense of it. You’ll want one if:

  • You already have centralized data, but no way to extract insights from it
  • You need dashboards, recurring reports, or executive-facing visualizations
  • Stakeholders are flying blind and asking for better visibility

Healthcare companies often hire BI engineers to track patient outcomes or operational performance. Consumer brands use them to understand campaign performance or customer churn. If your data exists but no one knows what to do with it, this is the role to hire.

Hiring either role too early can lead to a wasted budget. Hiring too late means missed opportunities. If you’re not sure where to start or need extra hands quickly, outsourcing your data engineering needs can be a smart way to fill the gap without overcommitting.

What if you need both? Planning for growth

Most growing businesses reach a point where they need both roles. Data engineers prep the data, and BI engineers extract insights from it. Together, they create the backbone for reliable, data-informed decisions.

But hiring both can be prohibitively expensive. This is especially true for mid-size and smaller companies and startups. In the US, salaries for just one role often exceed $140,000. Hiring both? That adds up fast.

That’s where nearshore hiring in Latin America becomes a real advantage. With annual salaries ranging from $42,000 to $84,000 for a data engineer, companies save around 50% compared to US-based hires (and the savings are the same for BI engineers). For many growing companies, it’s the difference between building a data team or holding off another year.

If that sounds like it might be the right move for you, our article “Why You Should Hire Nearshore Data Engineers and How to Do It” dives into the benefits of this approach (which apply to BI engineers as well).  

Team reviewing business intelligence and data engineering reports

Key Skills to Look for in BI and Data Engineers

Once you’ve figured out which role you need, the next step is knowing what to look for in a strong candidate. While BI and data engineers both work with data, the technical skills they bring to the table are quite different.

Skills for BI engineers

BI engineers focus on turning structured data into insights. Look for:

  • Data modeling to organize and structure data for analysis
  • SQL for querying databases and creating reusable views
  • Experience with BI tools like Power BI, Tableau, or Looker
  • A solid grasp of business logic and KPIs to build meaningful reports

They also need to work closely with decision-makers, so strong communication skills are a big plus.

Skills for data engineers

Data engineers have the skills to build the pipelines and backend systems that power everything else. Look for:

  • SQL and database development and management skills with tools like PostgreSQL, MySQL, or SQL Server
  • Experience with ETL and pipeline tools such as Airflow, Luigi, or Prefect
  • Programming knowledge in Python, Scala, Java, or shell scripting
  • Familiarity with APIs for data extraction or integration

Because data engineers often work across departments, collaboration skills matter here too. A great hire isn’t just a technical one. They should also know how to support the bigger picture.

Final Thoughts

If you’re still piecing together raw data from multiple sources, start with a data engineer. If your data is in place but no one can explain what it means, a BI engineer can bring clarity.

The roles are different, but both are essential. Knowing which is which can help you avoid bottlenecks, missed opportunities, and wasted budget. 

Of course, hiring for both roles can get expensive fast. That’s why more companies are turning to hiring remote data talent. If you’re ready to scale smarter, get expert hiring guidance in our guide on how to hire a remote data engineer. This way, you can take the next step with confidence.

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