OpenAI Data Engineer Interview Guide

The reported OpenAI Data Engineer onsite is organized around four distinct conversations: project experience, cross-functional collaboration, a hiring-manager discussion, and data infrastructure. Your project walkthrough should be both concise and technically deep. Be ready to explain what you built, the decisions you made, the tradeoffs involved, and how you handled follow-up questions rather than relying on a high-level project summary.

The cross-functional conversation is especially relevant for candidates who usually frame their work only through infrastructure. The account describes it as more straightforward when the candidate could communicate with a PM, align on goals, and explain tradeoffs clearly. Practice translating a technical decision into its effect on a product or team objective, including what you would prioritize when requirements conflict.

The dedicated data-infrastructure conversation is the clearest technical focus in the report, so prepare examples that demonstrate how you reason about data systems and their operational tradeoffs. The hiring-manager conversation may focus on fit and how you would work within the team; connect your examples to collaboration as well as technical ownership. This guide is based on one preparation account, so the ordering and exact emphasis of conversations may vary.