One Airbnb Data Engineer candidate reports a SQL and Python take-home followed by a broad virtual onsite covering coding, data modeling, system design and behavioral rounds. Another describes live data coding rounds. Here is how to prepare.
$190K
Avg. Base Comp
$350K
Avg. Total Comp
5 rounds
Typical Rounds
Not reported
Process Length
For Airbnb data engineer interviews, the clearest account describes a SQL-heavy take-home followed by a five-round virtual onsite. That candidate reports a HackerRank assessment with 3 to 4 SQL questions and 2 Python questions. The onsite then included DSA-style coding, a more general coding round, data modeling, a behavioral round and an end-to-end system design round. That candidate did not receive an offer and described the live coding rounds as the hardest part, with little room to wander.
A second candidate describes a data coding round that felt practical: a scenario-based problem of medium difficulty that they solved fully. A separate coding round centered on dictionary-based data manipulation and needed two loops. Time ran out before the second loop was finished. The interviewer was helpful and worked through a couple of errors with the candidate, so narrating your approach seems worthwhile, but pacing matters just as much. That candidate was still waiting on an outcome.
In practice, split your preparation. Practice timed SQL sets alongside Python data manipulation with loops and dictionaries, and aim to finish each problem with time to spare. Also rehearse explaining a data model and an end-to-end pipeline design aloud, focusing on tradeoffs and structure rather than syntax. Don't prepare only for algorithm problems, because the reported onsite also tested modeling, architecture and behavioral skills. Only a small number of reports exist, so expect some variation.
Synthesized from 3 candidate reports by our editorial team.
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Real interview reports from people who went through the Airbnb process.
The first thing I had to do was a take-home HackerRank, and that set the tone pretty quickly. It had 3 to 4 SQL questions and 2 Python coding questions, so it was less about chatting through my background and more about whether I could just get through the work cleanly and efficiently. After that, I moved into a virtual onsite with five rounds. The mix was pretty broad: one round on DSA-style coding, one more general coding round, one data modeling round, one behavioral round, and one end-to-end system design round. It felt like they were trying to cover both hands-on implementation and the bigger picture of how I think about data systems.
The hardest parts for me were the coding rounds because they were live and there wasn’t much room to wander. The data modeling and system design rounds were also important, but they were more about explaining tradeoffs and structure than grinding through syntax. I appreciated that the process was fairly well-rounded, but it was definitely a lot to prepare for because each round tested something different. I didn’t get an offer in the end, so my main takeaway is to be ready for a SQL-heavy take-home and then a very broad onsite that includes both coding and architecture, not just one or the other.
Prep tip from this candidate
Drill timed SQL take-home style problems with 3 to 4 queries plus a couple of Python tasks, then practice explaining a data model and an end-to-end system design out loud. Don’t focus only on DSA, because the onsite also included a separate general coding round and behavioral round.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Airbnb
Write a query that returns all neighborhoods that have 0 users.
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Synthesized from candidate reports. Individual experiences may vary.
One candidate reports starting with a take-home HackerRank containing 3 to 4 SQL questions and 2 Python coding questions. It appears to emphasize getting through the work cleanly and efficiently. Practicing timed SQL sets alongside a few Python tasks is a sensible way to prepare.
The same candidate reports one DSA-style coding round and one more general coding round during the virtual onsite, calling these the hardest. A second candidate describes a dictionary-based data manipulation problem needing two loops, where time ran out before the second was finished. Pacing and narrating your approach may help.
One candidate reports a data modeling round and an end-to-end system design round in the onsite. They describe these as more about explaining tradeoffs and structure than syntax. Preparing to talk through a schema or pipeline aloud, including choices and alternatives, would typically be useful.
The candidate who reported five onsite rounds says one of them was behavioral. No specific questions were reported for it. Applicants typically prepare a few concrete project stories covering ownership, collaboration and tradeoffs, so they can answer without improvising.
