What does it mean for a data pipeline job to be idempotent and why is it important?

Idempotent jobs can run multiple times without changing the final result. This matters because retries and reprocessing are normal. Techniques: - Use deterministic outputs - Write to staging then swap - Use upserts/merge with keys Idempotency reduces data corruption risk and makes backfills safer and faster.