Data & BI Engineer | Microsoft Azure, Databricks, Power BI, and AI Analytics

I design and build production-grade data platforms on Azure and Databricks. From Lakehouse architectures and streaming pipelines to enterprise BI and AI on governed data.

My experience spans across various aspects of Data Platform engineering:

Design secure Azure data platforms for analytics and AI, including landing zones, storage, identity, networking, governance, and cost control across Azure Data Services, Synapse, Data Factory, and Microsoft Fabric.

Build Databricks Lakehouse architectures with incremental pipelines, medallion models, data quality checks, and automated orchestration using Delta Lake, Auto Loader, Delta Live Tables, and Unity Catalog.

Implement streaming data pipelines for events, telemetry, and operational analytics using Event Hubs, Kafka, and Spark Structured Streaming to power near-real-time dashboards, alerts, and KPI monitoring.

Deliver enterprise Power BI semantic models with performant DAX, governed metrics, row-level security, incremental refresh, and deployment pipelines for reliable self-service reporting at scale.

Modernize legacy data and BI platforms by migrating workloads from SAP BW, Oracle, SSIS, SSAS, SSRS, and SQL Server into Azure, Fabric, and Databricks-based architectures.

Apply AI to governed enterprise data with RAG, vector search, Azure OpenAI, and MLflow to enable AI-assisted analytics, knowledge retrieval, and practical use cases with measurable business value.

I am always looking for new challenging projects and opportunities. If you're in need of a reliable, maintainable and future-proof data platform solution, reach out to me and let's discuss your ideas.