Real Data, Fake Patients
A hard Pipeline Design mock interview question on DataDriven. Practice with AI-powered feedback, real code execution, and a hire/no-hire decision.
- Domain
- Pipeline Design
- Difficulty
- hard
- Seniority
- L6
Interview Prompt
Our data engineering team works with protected health information in production, and engineers need realistic data in a separate development account without ever touching real patient records. Design a scheduled pipeline that ingests from production and de-identifies PHI across many foreign-key-related tables, replacing stable identifiers with synthetic tokens drawn from a consistent mapping so the same real id always resolves to the same token in every table, and landing a statistically representative dataset in the dev account's object store. The mapping lives in a vault that feeds only the de-identification step and that engineers cannot read; an orchestrator coordinates each refresh through the tables in dependency order, clears every column through a classification check before anything reaches dev, and writes a durable per-run audit log retained for years to satisfy HIPAA.
Summary
Dev needs production data. HIPAA says absolutely not.
How This Interview Works
- Read the vague prompt (just like a real interview)
- Ask clarifying questions to the AI interviewer
- Write your pipeline design solution with real code execution
- Get instant feedback and a hire/no-hire decision