Practical write-ups on data engineering, Microsoft Fabric, Azure, and lessons learned from building enterprise data platforms.
A deep dive into designing Bronze, Silver, and Gold layers on Microsoft Fabric OneLake — covering ingestion patterns, Delta Lake best practices, and Direct Lake semantic models.
How to build a reusable, configuration-driven pipeline framework in Azure Data Factory that handles 50+ source-to-target mappings without code duplication.
Implementing robust watermark-based state tracking in PySpark to ensure idempotent, fault-tolerant incremental pipeline execution at enterprise scale.
Practical T-SQL optimization strategies — columnstore indexes, query hints, statistics management, and execution plan analysis for large-scale data warehouses.
A practical guide to implementing Microsoft Purview across Azure Data Lake, Synapse, and Fabric — covering scanning, classification, lineage, and business glossary.
Reflections on 6+ years in enterprise data engineering — the skills that mattered most, the mistakes I learned from, and what I wish I knew earlier.
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