Two DAGs are glued by a time offset: the orders DAG schedules at 2am and usually finishes by 2:45am,
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
Two DAGs are glued by a time offset: the orders DAG schedules at 2am and usually finishes by 2:45am, and the marketing DAG schedules at 3am hoping the upstream is done. When the orders DAG runs slow and finishes at 3:15am, the marketing DAG already started at 3am and read stale state. Apply the cross-DAG framing this section just taught and replace the time offset with an asset trigger. The asset is structurally a lakehouse-format table (Iceberg, Delta, or Hudi) that the orders DAG writes and the marketing DAG reads; the lakehouse format gives the table snapshot semantics that asset-aware orchestrators trigger on. Replace the existing plain Snowflake mart with a lakehouse-format table; add a second orchestrator (or use the same orchestrator's asset-trigger feature) so the marketing DAG fires when the asset is fresh.
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