OpenAI's data roles are product-analytics heavy: usage cohorts, retention curves, sessionization, and experiment readouts. Practice those exact SQL shapes on runnable datasets with AI tutoring.
21 challenges
OpenAI-pattern set
Real datasets
Usage-event tables
AI tutor
Step-by-step hints
The 21 challenges tagged OpenAI in the SQL Quest bank, with every raw challenge tag resolved to the 9 canonical skills. Each share is the portion of those 21 challenges that exercise the skill — a challenge exercises several, so the shares do not sum to 100%. This is the composition of the practice set on this page, not a measurement of OpenAI’s interview.
These are SQL Quest challenges chosen because their SQL matches the work — Querying Basics, Window Functions, Aggregation & Grouping. They are not questions OpenAI has asked, and this page does not claim to know its questions. All of the six play free; each card opens the challenge itself.
General guidance about analytics SQL work — not sourced from OpenAI and not a description of its process. We have no dated, citable source for how OpenAI runs its SQL round, so this page states none.
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Interviewing at more than one company? The same patterns carry: Anthropic · NVIDIA · Databricks — or the full company-by-company interview guide.