How to Land A Job As An Analytics Engineer

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Have you heard of the hottest new role in the data world? It’s a combination between a data analyst and data engineer, with business skills to support marketing and growth teams.

If you guessed analytics engineer, you are correct! And you must’ve read my previous article on the analytics engineer job description where I talk about the differences between an analytics engineer vs data engineer.

While I talked about the key skills of an analytics engineer in that article and how it varies from its similar counterparts, here I want to give you actionable advice on what you can practice starting today. After all, practice makes perfect! Especially when it comes to anything technical.

Analytics Engineer Skills

SQL

You won’t be able to get by as an analytics engineer if you aren’t a SQL master. This is the top technical skill that you will be interviewed in, so you want to make sure you really practice it. I find practicing for an interview makes you 10x better at any SQL you do daily on-the-job anyways, so it’s a win-win scenario.

You want to practice problems ranging from easy aggregates and joins to more complex CTEs and window functions. While most companies may not expect you to know window functions, they are always helpful to have in your SQL toolkit. You’ll probably have to google them at some point in your career, so mine as well learn them now.

While aggregates and joins are considered the more basic, easier parts of SQL, you will be expected to really understand how they work. Make sure you practice sum vs count, using these with group bys, and explaining the difference between left join and join.

If you aren’t familiar with SQL at all, but want to learn, check out the SQL tutorial from W3Schools. That will teach you all of the basics and let you play around with some different functions.

For problems that mimic real interview problems, my go-to is Leetcode. And don’t let the $35 monthly price tag scare you. Use it for the months before/during the interview process and then cancel it. It’s totally worth the money!

Data Modeling (dbt)

Data modeling is a huge part of an analytic engineer’s role. This often goes hand-in-hand with a tool called dbt, or data build tool. This is a tool that compiles your SQL queries in a reproducible, easy-to-read way.

While it is a fairly new tool, it is one that is on the rise because it makes life so much easier and more organized. No more rewriting the same blocks of code over and over again! If you want to learn more check out my article What is dbt?.

Knowing dbt isn’t necessary for an analytics engineer, but it is a huge advantage to have on your resume. If you’re applying for this role, chances are you will be expected to learn dbt at some point. The company that made the tool is actually known for crafting the analytics engineer position.

I highly recommend looking through the documentation on their website and going through some of their tutorials. The more you read and watch, the more you will understand its role in the data stack.

Presenting your findings

This is another key skill in both the interviewing process as well as the day-to-day job. Lots of companies expect you to complete a data project and then present your findings to the team. This is the part of the interview that makes or breaks a lot of candidates.

First, make sure you are showing compelling visualizations that actually communicate the solution to the problem at hand. Nobody cares about visualizations that are pretty or “cool” if they don’t tell a story related to the problem. Also, make sure they are actually readable.

Second, dig deep into the data. Think of all the different outcomes that the data could be pointing you towards. When you have a lot of data, there usually isn’t just one simple solution. There are pros and cons to all potential outcomes.

Third, be confident! You probably spent a lot of time on whatever analysis you are presenting. Be proud of the work you’ve done and confident in the solution that you found. Fake it to you make it really works, especially when you have data to back it up (hehe).

Presenting is definitely an art that takes practice. Don’t be afraid to apply to jobs you may not even want, just for some extra practice. Interviewing is scary but the only way to get better at it is do it more often. Also, practice in front of your spouse, friends, or mom! Someone is better than no one.

Conclusion

Just like any other career, analytics engineering takes work. If you put the time in to learn the core skills, you can land a job that will end up teaching you much more. Analytics engineering is one of those careers where you learn exponentially when on the job.

You will continue to use your SQL, data modeling, and presentation skills every single day, while also diving deeper into complex problems. Some problems you just can’t “practice” until they hit you right in the face.

Work on these core skills and chances are you’re ahead of everyone else. Don’t stop trying until you feel confident! Good luck!