What type of resource were you using to transform raw files from bronze to silver to gold layers?

In a lakehouse architecture, the transformation from bronze (raw) to silver (cleaned) to gold (curated) layers is typically performed using an ELT engine such as Apache Spark running on Databricks or AWS Glue. These resources provide distributed compute, support for Spark SQL, and integration with the underlying storage (S3, ADLS). The process involves reading raw Parquet/CSV files from the bronze layer, applying data quality checks, deduplication, and schema enforcement to produce the silver layer, and then aggregating or enriching the data to create the gold layer for analytics. Spark jobs can be scheduled via Airflow or Glue workflows, and the code is often version‑controlled in GitHub. This approach allows iterative development, easy scaling, and the ability to re‑run transformations on new data.