At IBM, I lead data engineering and BI delivery for pharma supply-chain and automotive analytics platforms, designing production Azure Data Factory and Databricks pipelines processing 2–4 TB of data daily. I also deliver Power BI datasets, dashboards, and paginated reports that help stakeholders track inventory, shipments, SLAs, warranty trends, and dealer performance.
I reduced Power BI refresh times from 80 minutes to 20 minutes by redesigning semantic models, tuning DAX, and partitioning fact tables. I’ve also cut SQL Server reporting runtimes by up to 60% and reduced daily ingestion windows from more than four hours to under 45 minutes using watermark-based incremental loads and Delta merges.
Previously at Accenture, I built and maintained 40+ Azure Data Factory pipelines and SQL warehouse solutions supporting analytics for 200+ business users. I deployed SQL, tabular models, and ARM templates through Azure DevOps CI/CD while improving warehouse load times for 100M+ row workloads.
I enjoy turning ambiguous business requirements into dependable dimensional models and self-service analytics. I mentor engineers on Databricks, PySpark, Power BI, performance tuning, and modular pipeline design.
