I started interviewing for analytics engineering roles around 2020. Analytics engineering hadn’t been around long, so there weren’t many guides, blogs, or general tips and tricks on how to navigate recruitment for that role. Even now, a quick Google search of “analytics engineer interviews” gives about five relevant results. So, if you’re looking to break into this field, here are some insights on what to expect in your next interview.
Recruiter round
This is normally a short interview with a (technical) recruiter. Usually, the recruiter just wants to learn more about you beyond your resume, but they also give you a chance to learn more about the company. Take advantage of this time to scope out more details about the company, because as much as you are being interviewed, you are also interviewing the company. When you are conversing with a technical recruiter, you may get asked for more specifics about your technical capabilities. For example, describe the most complex macro you have built using dbt.
Technical round
This usually comes in one of two forms: a take-home assessment or live peer coding.
A take-home assessment can really vary in scope and effort. In my experience, the take-home assessment is aimed at measuring both your technical fluency, usually in SQL, and your analytical abilities in deriving some insights from a set of data. I’ve never had a take-home assessment that took more than a few hours, but there are horror stories of take-home cases taking days to complete.
Here are some examples of take-home assessments I’ve received in the past:
- Perform some SQL analysis on a BigQuery public dataset, and visualize some insights in Google Data Studio
- Calculate a series of metrics in Jupyter notebook using Python and SQL
With a live peer-coding session, you’re usually paired up with another analytics engineer (or possibly other members of the data team) to run through some technical assessments. You’re mainly going to be tested in SQL, but you may be asked to code in other relevant languages. Practice your SQL through Leetcode, HackerRank, or InterviewQuery.
Be prepared to run through questions that require knowledge of CTEs, window functions, joins, and various aggregations. Usually, the SQL dialect you know won’t matter too much, but it’s always good to check in with your interviewer before starting! I had a coding assessment that used PostgreSQL, and there were minor syntax differences that I got help with from the interviewer. Trust me in that no interviewer is looking to set you up for failure, but it’s better to communicate any issues you foresee upfront.
Analytics round
If you didn’t have a take-home assessment, chances are you will have a live analytics case. You’ll likely be playing the role of a data detective where your goal is to take some raw data and try to make some sense of it. You might be given a specific prompt, but sometimes it’s up to you to figure out what’s a fruitful finding to share.
In one of my analytics interviews, I was given a series of tables and a high-level description of what the tables contain. Then, I was tasked with pointing out which columns I thought would be important for further analyses, and what kind of metrics I would develop from them. Sounds quite vague, right?
In a subsequent scenario, I was given a graph that displayed orders month over month and was asked to identify why I believe orders for a specific period were lower than average. I was given a few aggregated metrics for that period, and the dbt model that derived the metrics. Part of playing the role of a data detective is to ask questions along to way since the data itself might not have enough context.
Conclusion
Every company has its own setup for interviewing for analytics engineering roles, so be prepared to tackle all three rounds, if not more. Leading up to recruitment, I always spend time refreshing my SQL skills, arming myself with the latest analytics engineering know-hows, and practicing my communication and presentation skills. It will take work but preparing yourself for these interviews will pay dividends when you land the job, as these skills will carry forward.
Good luck!
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