Recommendations Now, Royalties Later
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
- Seniority
- L5
Interview Prompt
We operate a streaming service with thousands of titles across licensed and original content, and viewer engagement events must reach our recommendation system in near-real time while our content acquisition team needs daily reporting on which licensed titles are delivering value. These two consumers share the same underlying event data but have distinct latency and exactness requirements. Design a streaming pipeline that serves both efficiently.
Summary
The catalog updated. Did anyone notice?
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