One Airflow instance owns a 60-task mega-DAG spanning three teams: ingestion, analytics-engineering
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
One Airflow instance owns a 60-task mega-DAG spanning three teams: ingestion, analytics-engineering curation, and ML feature extraction. When the analytics dbt step fails, the unrelated ML feature extraction halts and pages cross team lines all night. Apply the section's split-DAG framing and split the orchestrator along ownership boundaries so a failure in one team's branch does not halt unrelated work in another.
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