What it Takes to Become a Business Intelligence Engineer at Amazon

Python, Matlab, and R to model data!?

I’m constantly asked about the difference between a business intelligence engineer and an analytics engineer.

According to Glassdoor, “(Business intelligence engineers) create dashboards, databases, and other platforms that allow for efficient collection and evaluation of BI data”.

Like with any role, the responsibilities and skills required depend on the exact role.

As an analytics engineer, I find I rarely interact with our BI tool. If I do, it’s to ensure I’m not breaking any dashboards downstream of a data model I’m changing.

However, not all analytics engineering roles allow you to avoid the BI layer entirely. Again, it depends on the specific role.

If you want to explore some of the main differences between BI engineers and analytics engineers, I invite you to check out a post I wrote comparing the two.

Today we’ll look at two Business Intelligence Engineer roles, one for NA Sales & Marketing, and the other for Advertising Finance. Interestingly enough, the skills and experience required for both roles are exactly the same.

Despite different business domains, each requires 3+ years of experience with data visualization, data modeling, statistical analysis, Python scripting, and AWS solutions.

In some ways, it’s comforting to know that you can apply for any Business Intelligence Engineer position within Amazon and the requirements will be the same. This is most likely due to corporate protocol with crafting job descriptions and landing on a role title/level.