A row-count check authored in test passes cleanly there and fires repeatedly in production for reaso
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 row-count check authored in test passes cleanly there and fires repeatedly in production for reasons unrelated to data quality. Test fixtures load the same rows daily; production carries live traffic with calendar effects. The section's discipline: keep the assertion identical across environments and load thresholds from environment-specific config. The opposite mistake (a check that passes in production because the threshold matches whatever the producer is currently emitting) is also wrong because it cannot detect drift. Compare dev vs prod thresholds by replacing the single quality-check transform with one whose name states the shared assertion plus environment-aware threshold sourcing (config keyed on environment).
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