Production-Grade ELT: Airflow + dbt + a Cloud Warehouse End to End

<p>Fernglow Outdoor Supply's data pipeline was six independent cron jobs, a maze of unreviewed SQL views, and no way to tell a silent failure from a healthy run -- until a broken extractor made an entire region's sales look negative on a Monday morning dashboard. This capstone follows data engineer Priya Nandakumar as she rebuilds that pipeline into a real production system: an Airflow DAG that orchestrates dbt Core runs with proper task dependencies, dbt tests wired in as gates that block bad data before it reaches BI tables, incremental models with safe, parameterized backfills, and the SLAs, freshness checks, and on-call alerting that let the team find out about problems in minutes instead of from an angry regional manager. Every lesson ships real, runnable Airflow DAG code and real dbt SQL, built around the actual incidents that forced each design decision.</p>

Tools: Apache Airflow, dbt Core, Snowflake, Python, SQL, Slack, PagerDuty