This one's for building and maintaining data pipelines with the modern stack: dbt, Airflow, Spark, Kafka. It pushes the medallion architecture pattern (Bronze/Silver/Gold layers) and emphasizes data quality gates at every step. The anti-patterns section is genuinely useful, calling out stuff like full table refreshes and hardcoded dates that I've seen break production pipelines. Comes with reference examples for complete dbt projects, Airflow DAGs with sensors, and Spark streaming jobs. The quality checklist is comprehensive without being preachy. If you're doing ETL work beyond basic scripts and need structure around incremental processing, orchestration, and data testing, this gives you that framework.
npx skills add https://github.com/erichowens/some_claude_skills --skill data-pipeline-engineer