Bronze data layer promised 'just dump the CSV'—now it's a typo-fixing, header-hunting vendor wrangling beast after two labs send schema chaos

In a recent presentation at PyBay 2025, a data engineer discussed the challenges of managing schema chaos in the bronze layer of the Medallion Architecture. The bronze layer, intended for raw data with minimal transformation, became increasingly complex when dealing with real-world data quality issues from vendors. Vendor A and Vendor B provided CSV files with different column names and structures, requiring standardization functions and vendor-specific logic. As more issues arose, such as typos, metadata rows, and special characters, the ingestion pipeline grew to include fuzzy matching, header detection, and character sanitization. The engineer questioned whether the resulting bronze layer, with eight transformation steps and vendor-specific branches, still qualified as "raw data." With the arrival of new vendors and potential issues like date format differences and unit conversions, the engineer highlighted the need for a more robust solution, potentially by redefining what "raw" means and treating column names as data rather than schema.