BI vs Analytics Engineer

Which is right for you?

It’s a constant debate over who does what in the data world.

Some people go red in the face arguing that analytics engineers are just another flashy, confusing way of saying data analyst or data engineer. Others, like me, believe differentiation is crucial for matchmaking the right companies with the skilled people they need and vice versa.

There’s a reason there are up to 20 different ways to call someone an engineer. Simply calling them an engineer is not descriptive enough of their skill sets and everyday work! This is why it’s helpful to have different titles for different data people, not just your typical data engineer, data scientist, and data analyst.

BI engineers and analytics engineers are two of these data titles that are often confused. Is analytics engineer a different term for BI engineer, or vice versa? Which makes the most sense for you and what you want to accomplish in your career?

Let’s look at how each of these is defined in the job market.

What is a BI Engineer?

According to Glassdoor,

“They create dashboards, databases, and other platforms that allow for efficient collection and evaluation of BI data”.

Jamie Zhang, a business intelligence engineer at Amazon, says her primary responsibilities are reporting on KPIs, enabling self-service data solutions, database migration, and database modeling.

According to Analytics Insights, “

[BI Engineers’] primary role revolves around getting data into an accessible infrastructure so that analysts can grab it for getting insights”.

When looking at job descriptions, these were the skills that repeatedly appeared:

• SQL

• Extensive experience using BI tools (Looker, Tableau, etc.)

• Python

Some of the job descriptions I saw were almost identical to that of an analytics engineer. They included data modeling and data warehousing as a huge portion of the responsibilities.

However, some of the others focused heavily on the presentation of data. Rather than building data pipelines and focusing on architecture, they emphasized solving business problems with data.

What is an Analytics Engineer?

According to dbt, the inventors of analytics engineering, an analytics engineer:

“…provides clean data sets to end users, modeling data in a way that empowers end users to answer their own questions.While a data analyst spends their time analyzing data, an analytics engineer spends their time transforming, testing, deploying, and documenting data”.

While this is a great definition, I don’t think it exactly covers everything that I find myself doing as an analytics engineer.

I repeatedly find myself utilizing the following skills:

• SQL

• Data modeling

• Data warehousing

• Quality testing

• Data pipelining

Unlike a BI engineer, I don’t use BI tools frequently, if at all. Instead, I own the entire stack from ingestion to transformation, focusing on producing high-quality data for analysts to use.

The Main Difference

Honestly, it depends. Probably not the answer you wanted to hear, and definitely not the answer I wanted to give, but the truth. Nowadays there is a lot of overlap between the different data roles and how they are classified.

A data engineer at one company could be an analytics engineer at another.

A data analyst at one company could be a BI engineer at another.

A BI engineer at one company could be called an analytics engineer at another.

That’s just how it goes. So, instead of paying attention to titles, maybe we can agree to focus on the skills and experiences of a role instead?

Let’s recognize that there is overlap and we are all doing the best we can to define what we spend our days doing.

Conclusion

BI engineers and analytics engineers are different but maybe only slightly, depending on the person and the company.

Some job postings may be titled “BI engineer” but actually fit closer to that of an “analytics engineer” and vice versa. Instead of getting caught up in the titles, focus on the skills and experiences.

Analytics engineers- look out for postings mentioning data warehousing, data modeling, and dbt.

BI engineers- look out for postings mentioning dashboarding and Python but also data warehousing and data modeling.

And, if you want to let me know your thoughts, I’d be more than happy to listen!

Have a great rest of your week!

Madison Mae

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