Anup T.

⚡ Expert-Vetted (Top 1%) on Upwork. Top Rated Plus. 100% Job Success. 15+ years architecting enterprise data platforms on Microsoft Fabric and Azure.

If your data platform is fragmented, expensive, slow, or not ready for AI — I help you modernize it into a scalable, governed, business-ready cloud data ecosystem.

I'm a Strategic Azure Solutions Architect and Data Engineering Leader. I work with clients who need more than development help — they need someone who can assess the current state, define the right architecture, build the roadmap, guide implementation, and stay hands-on when needed.

🎯 What I help you solve
✓ Modernize legacy SQL Server, SSIS, Oracle, and on-prem data platforms
✓ Design Microsoft Fabric Lakehouse, Warehouse, OneLake, and Direct Lake architectures
✓ Build scalable Azure Data Factory + Databricks ingestion and transformation frameworks
✓ Improve Power BI performance, semantic models, RLS, and enterprise BI adoption
✓ Reduce cloud cost through better architecture, workload design, and optimization
✓ Prepare your data foundation for AI, Copilot, Fabric Data Agents, and self-service analytics
✓ Deliver governed data solutions for regulated and complex enterprise environments

🧩 Microsoft Fabric expertise
Hands-on experience with Microsoft Fabric implementation, solutioning, and roadmaps:
▸ Fabric Lakehouse, Warehouse, OneLake, Notebooks, and Pipelines
▸ Direct Lake semantic models and Power BI optimization
▸ OneLake shortcuts and DB mirroring patterns
▸ Fabric Data Agent and Copilot proof-of-concepts
▸ Self-service data models in controlled enterprise environments
▸ Data franchise models for governed, business-owned analytics

If you're deciding whether to move to Fabric, how to structure workspaces and domains, how to combine Fabric with Databricks, or how to design an AI-ready data platform — I can help you avoid costly architecture mistakes early.

🛠 Azure data engineering expertise
▸ Azure Data Factory pipeline design and metadata-driven frameworks
▸ Azure Databricks, PySpark, Spark SQL, Delta Lake, and performance tuning
▸ Azure Data Lake Gen2, Synapse Dedicated Pool, Azure SQL, and SQL Server
▸ Batch and near-real-time data processing patterns
▸ Data warehouse, lakehouse, staging, ODS, and data mart design
▸ Star schema, snowflake schema, dimensional modeling, and semantic layer design ▸ CI/CD, DevOps, environment strategy, and production support readiness