A technical data governance engineering lab showing how metadata, lineage, data quality, access controls, and stewardship workflows can be embedded into a cloud-style analytics platform.
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Updated
May 12, 2026 - Python
A technical data governance engineering lab showing how metadata, lineage, data quality, access controls, and stewardship workflows can be embedded into a cloud-style analytics platform.
Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. Portfolio piece, MIT, synthetic data only.
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