Data Warehouse / BI Stack (dbt, BigQuery, Metabase/Looker, Python, Airflow) overview

A modern data warehouse and business intelligence stack where Airflow orchestrates ELT pipelines that land raw data into BigQuery, dbt transforms it into dimensional models with tested, documented SQL, and Metabase or Looker provides self-serve dashboards and ad-hoc exploration for business stakeholders. Python scripts handle custom data source connectors and quality checks. SQL is the primary modeling language across the stack. Designed for data teams in growth-stage companies building their first production analytics layer. The tradeoff is warehouse cost management — BigQuery's on-demand pricing can spike unpredictably with poorly optimized queries, requiring careful slot reservation planning and query governance as usage scales.