databricks-etl-pyspark-notebooks

Build, deploy, and orchestrate ETL pipelines on Databricks using PySpark notebooks (.ipynb). Use when: creating ETL pipelines, building medallion architecture (silver/gold), writing PySpark transformations in notebooks, scheduling notebook-based data pipelines, deploying ETL jobs with Declarative Automation Bundles, configuring serverless or classic compute for ETL workloads, writing to Delta or Iceberg tables. Assumes source data already exists as tables in Unity Catalog. Triggers: ETL, ELT, extract transform load, PySpark, spark notebook, medallion, silver gold, data pipeline, transform, aggregate, data engineering, Delta Lake, Iceberg, data lakehouse, notebook job, ETL job, Delta merge, SCD.