DATA & AI ENGINEER
Precision data platforms that make intelligent decisions feel calm.
I partner with data leaders to architect Azure-native analytics, automate Databricks delivery, and shape Power BI products that stay explainable as AI scales. Every layer is designed for clarity, governance, and teams that move quickly.
ENGAGEMENT NOTES
- [01]Design Azure lakehouses with governance, observability, and cost discipline baked in.
- [02]Operationalize Databricks notebooks, jobs, and Unity Catalog so ML and BI stay in sync.
- [03]Ship Power BI experiences that surface the signal for executives without drowning teams in noise.
Latest posts
VIEW ALLBuilding a Production-Ready Data Pipeline with Azure (Part 9): Migrating from Synapse Serverless SQL
Aug 23, 2025Plan the migration from Synapse Serverless SQL to Microsoft Fabric with workload mapping, architecture decisions, and cutover strategy.
[11]Building a Production-Ready Data Pipeline with Azure (Part 8): Enterprise Row-Level Security
Aug 13, 2025Enforce enterprise row-level security across Power BI, Unity Catalog, and Fabric with dynamic territories and auditing.
[10]Building a Production-Ready Data Pipeline with Azure (Part 7): Power BI Integration with Synapse
Aug 09, 2025Surface Azure Synapse and Databricks datasets in Power BI with DirectQuery patterns, caching tactics, and cost controls.
Building a Production-Ready Data Pipeline with Azure (Part 6): Operationalizing the Gold Layer
Jul 20, 2025Model the gold layer with dimensional design, scheduling strategies, and dependency management for trustworthy business datasets.
[08]How to Use Databricks SET/UNSET MANAGED in a Metadata-Driven Framework
Jul 11, 2025Automate Databricks SET/UNSET MANAGED conversions to boost performance and cut costs with a metadata-driven control plane.
[07]Building a Production-Ready Data Pipeline with Azure (Part 5): Implementing CI/CD
Jun 30, 2025Implement Azure Data Factory and Databricks CI/CD with Git integration, DevOps pipelines, and automated environment promotion.