reviewing-data-pipeline-code

Review data engineering pull requests with a data-specific checklist — idempotency, correct grain, incremental logic, cost impact, data quality tests, PII handling, and backward compatibility — that generic code review misses. Use when reviewing a dbt/SQL/Spark/Airflow PR, a data pipeline change, or a new model, and you want to catch data-correctness and cost issues before merge.