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.
$250K
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 focused on how you think — about metrics, about systems, and about the people who consume data. The homework presentation is the clearest signal of this. It's not a portfolio show-and-tell; it's a structured interrogation of your decision-making. Candidates who treat it as a formality get caught flat-footed when interviewers probe the why behind every design choice.
The pipeline design question — specifically around monthly active users — is deceptively simple. MAU sounds like a standard metric, but the real test is whether you can surface the ambiguities: What counts as 'active'? How do you handle late-arriving data? What does the downstream consumer actually need? A recurring theme in this process is that OpenAI wants engineers who define the problem before they solve it. That instinct matters more here than raw technical fluency.
The stakeholder rounds are also worth taking seriously. At a company where the product is moving this fast, the ability to translate data work into decisions for non-technical partners isn't a soft skill — it's a core job requirement. We'd expect OpenAI to weight this heavily given how cross-functional the data function needs to be in a high-growth AI environment.
Synthetized from 1 candidates reports by our editorial team.
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Real interview reports from people who went through the OpenAI process.
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.
The process had five main touchpoints:
Initial conversation (1 hour) — with the hiring manager. More of an intro/screening conversation.
Homework assignment — Choose a project you've previously worked on and prepare a presentation around it.
Homework presentation (45 minutes) — Walk through the project you chose. They asked questions throughout and at the end, not just a one-way presentation.
Two technical rounds — A mix of hands-on SQL and higher-level pipeline design thinking.
Two stakeholder rounds — More conversational, focused on how you work with cross-functional partners and communicate data insights.
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.
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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Sourced from candidate reports and verified by our team.
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.
Candidates choose a past project they've worked on and prepare a presentation around it. The project should be something you know deeply, as it becomes the centerpiece of the next round.
A walkthrough of the project you selected for the take-home. Interviewers ask questions throughout and at the end, so be prepared to defend design decisions and discuss tradeoffs in depth.
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 architect a data 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.