data-engineering-best-practices

Data engineering best practices: medallion architecture, dataset lifecycle, partitioning, file sizing, schema evolution, and append/overwrite/merge patterns across Polars, PyArrow, DuckDB, Delta Lake, and Iceberg. Use when designing production data pipelines or reviewing data platform decisions.