Building Azure data pipelines that scale,
with precision, reliability, and zero drama.
2+ years turning messy, high-volume data into clean analytics infrastructure. Specialising in ADF, Microsoft Fabric, Synapse, PySpark, and the full Azure modern data stack — from raw ingestion to Power BI dashboards.
I'm a Data Engineer at LTIMindtree, Bengaluru, where I design and build cloud-native data infrastructure on the Azure ecosystem — primarily for the Microsoft Learn platform analytics workload.
My day-to-day involves translating complex, high-volume raw data flows into clean, reliable pipelines that business stakeholders can actually trust. That means ADF orchestration, PySpark transformations, Medallion Architecture on Microsoft Fabric, and Synapse Analytics SQL pools.
I care deeply about pipeline resilience — incremental loads, watermarking, trigger-based scheduling, SLA monitoring, and automated data-quality checks baked in from the start, not bolted on at the end.
Before that, I trained through the Great Learning Academy Software Development Program and completed a B.Tech in Computer Science at VIT Chennai. I hold a Microsoft AZ-900 certification and am continuously expanding deeper into the Azure data engineering certifications track.
Outside work: I enjoy reading about distributed systems, experimenting with Delta Lake, and contributing to internal knowledge-sharing sessions at my team.
Open to data engineering roles. If you're working on interesting data problems at scale — pipelines, lakehouses, real-time or batch — let's talk.