OpenAI Data Engineer interview typically runs 5 rounds: hiring manager screen, homework assignment, project presentation, technical rounds, and stakeholder rounds. The process spans roughly two months and is distinguished by a take-home project presentation central to evaluation.
$200K
Avg. Base Comp
$1170K
Avg. Total Comp
5-6
Typical Rounds
2-3 months
Process Length
From what we've seen in this process, OpenAI is less interested in whether you can write a perfect SQL query and more interested in how you think — about metrics, about systems, and about the people who consume your work. The homework presentation is the centerpiece of the loop, and candidates who treat it as a formality get caught off guard. They ask probing questions throughout, not just at the end, so you need to own every decision you made in that project: why you modeled data a certain way, what tradeoffs you accepted, what you'd do differently.
The pipeline design question — specifically around something like monthly active users — is deceptively simple. It's not a coding exercise. What they're probing is whether you can define a metric precisely before you build anything around it. What counts as "active"? What's the grain of the table? How do you handle edge cases in user behavior? The conceptual rigor matters more than the implementation details here.
The stakeholder rounds are a real part of the evaluation, not a formality tacked onto the end. OpenAI is a company where data work sits close to product and research decisions, and they want to know you can translate analytical thinking for non-technical partners without losing precision. Candidates who treat those conversations as soft filler tend to underperform. The whole loop is designed to see if you can hold your own across technical depth, system thinking, and communication — all three, not just one.
Synthetized from 1 candidates reports by our editorial team.
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Real interview reports from people who went through the OpenAI process.
# OpenAI — Analytics Engineer (Interview Experience) **Outcome:** Unknown **Format:** Virtual (assumed) **Interview Type:** Multi-round loop This was for an Analytics Engineer role at OpenAI. The interviews happened about two months before this was submitted. It was a pretty involved process with several rounds total. ### Interview Process The process had five main touchpoints: 1. **Initial conversation (1 hour)** — with the hiring manager. More of an intro/screening conversation. 2. **Homework assignment** — Choose a project you've previously worked on and prepare a presentation around it. 3. **Homework presentation (45 minutes)** — Walk through the project you chose. They asked questions throughout and at the end, not just a one-way presentation. 4. **Two technical rounds** — A mix of hands-on SQL and higher-level pipeline design thinking. 5. **Two stakeholder rounds** — More conversational, focused on how you work with cross-functional partners and communicate data insights. ### What Was Covered The technical rounds had two main question types: - **Traditional SQL** — Standard SQL, nothing too exotic. Just solid fundamentals. - **Pipeline design / system architecture** — The specific question was: how would you build a data pipeline to calculate monthly active users? So it's less about writing code and more about thinking through metric definition and pipeline structure at a conceptual level. The stakeholder rounds were conversational, not technical. Cross-functional communication and how you translate data insights for non-technical partners. ### Takeaways Know your homework project inside and out. It's a big part of the process and they ask a lot of questions during the presentation, so don't treat it as a formality. Also be ready to think through pipeline design at a conceptual level, things like how you'd define and compute metrics like monthly active users.
Prep tip from this candidate
The homework presentation is a major part of the process — they ask questions throughout and at the end, so pick a project you know deeply and can defend from multiple angles. For the technical rounds, brush up on traditional SQL fundamentals and be ready to walk through pipeline design for metric calculations like monthly active users at a conceptual level.
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Topics based on recent interview experiences.
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Synthesized from candidate reports. Individual experiences may vary.
An introductory conversation with the hiring manager that serves as an initial screening. Expect a mix of background discussion and role-fit questions.
Choose a past project you've worked on and prepare a presentation around it. This is a significant part of the process, so select a project you know deeply.
Walk through your chosen project with the interviewers. Expect questions throughout and at the end, so be prepared to defend decisions and go into detail on any aspect of the work.
Two rounds covering SQL fundamentals and pipeline design thinking. Expect standard SQL questions as well as conceptual system design questions such as how you would build a pipeline to calculate monthly active users.
Two conversational rounds focused on cross-functional collaboration and communication. Interviewers assess how you work with non-technical partners and translate data insights for broader audiences.