A marketing team computes revenue across hundreds of millions of rows by scanning raw Parquet in S3
A medium 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
- medium
Interview Prompt
A marketing team computes revenue across hundreds of millions of rows by scanning raw Parquet in S3 with Pandas; each query takes 18 minutes and there is no schema enforcement. Apply the section's data-warehouse framing and add the analytical layer between the lake and the dashboard, replacing the Pandas transform with a warehouse-native one so the columnar layout and separated compute give the speedup the section names.
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