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Data Engineer Intern Interview Experience
The first call was ten rapid-fire CS trivia questions, and they wanted one-word answers on the spot.
Interview process
I started with this intro call that was basically 10 rapid-fire technical trivia questions, and they wanted instant answers on the spot. After that, the process moved into the actual interviews. The Python round felt pretty easy because it was just short coding problems one after another, and once I finished one, they immediately pushed the next. The SQL round was the part that really stood out because it happened in an IDE with sample tables and an exact expected output. There was also a 45-minute behavioral in the mix before they made the decision.
- Phone interview
- Technical interview
- Other
Interview rounds
5 questions across 4 roundsPhone interview
1 questionOverview
This opener was weirdly fast. I got 10 on-the-spot trivia-style technical questions and they wanted short answers right away, not long explanations.
Question types asked
Specific questions asked
How do you get a binary tree in order?
I gave the kind of one-word answer they were looking for, like in-order traversal. That whole round felt like that: 10 pretty trivial questions where they just wanted me to answer immediately and move on.
Technical interview (1)
3 questionsOverview
The Python round felt pretty easy. It was a solve-as-many-as-you-can format where once I finished one question, they immediately moved me to the next.
Question types asked
Specific questions asked
I treated it like one of the easy questions in the set and just tried to get through it cleanly and fast. The feel of the round was more about pace because as soon as I finished, they pushed the next problem.
This was another standard easy-style question. I was mostly focused on finishing quickly because the format rewarded getting through as many questions as possible, not spending forever on one.
Same deal here. It was a familiar easy coding problem, and the round felt straightforward because they just kept advancing me to the next question after I finished.
Technical interview (2)
1 questionOverview
The SQL round was the one that stood out. They dropped me into an IDE with sample tables and an expected output, and it felt much closer to LeetCode hard than basic SQL screening.
Question types asked
Specific questions asked
Write a SQL query from one or more sample tables to match an exact expected output, like getting average order price by country and ordering countries alphabetically.
They put me in an IDE and gave me a prompt with example tables to work from, sometimes more than one table. Then I had to write the exact SQL query to produce the exact output they showed. A representative version is using something like orders and stores, finding average order price by country, and then sorting the countries alphabetically. That was the round that felt really hard.
Other
Overview
There was also a 45-minute behavioral in the process. I don't remember anything especially unusual about that part compared with the technical rounds.
Question types asked
Interview tips
I'd prep for the opener by getting really quick at the basic CS stuff, because they seem to want the answer right away, not a whole explanation. For Python, I'd just grind the standard easy patterns until they're automatic, like list traversal, median-type questions, two sum, and merging sorted lists. For SQL, I'd put way more time into writing exact queries on sample tables, especially anything with joins, averages, grouping, and ordering, because that's the part where the difficulty jumped for me.
Company culture
Speed was the big thing I took away. It felt like the expectation there is that if something needs to change, I'd be the one to unblock it and just go make it happen.
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More Meta interview experiences
“The interview is definitely hard, but achievable with preparation because the timing is very less. In the screening, you get five Python and five SQL in one hour, and you need to pass at least three SQL and three Python.”
“What stood out to me is that every loop round started with product sense, then I had to turn that answer into a data model, and from that they jumped straight into SQL and Python. One case was even an Instagram metric drop where I had to do root cause analysis live.”
