A pipeline on the canvas runs as a single monolithic Python task that does extract+clean+aggregate i
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 pipeline on the canvas runs as a single monolithic Python task that does extract+clean+aggregate inside one operator. The team is debating whether to add a single DAG-level retry that re-runs the whole DAG on any failure. Apply the task-DAG-run vocabulary this section just taught and reject the DAG-level retry approach. Retries operate on task instances (one task in one run), not on DAGs; re-running the whole DAG repeats successful work. Split the monolith into three distinct task nodes (extract_orders, clean_orders, aggregate_orders) so each retries independently when it fails. The orchestrator (already present) owns the schedule and the per-task retry policy; the structural split is what makes per-task retry meaningful.
How This Interview Works
- Read the vague prompt (just like a real interview)
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