About
Data Engineer with 4 years of experience building and modernizing scalable data pipelines and distributed data workflows using Python, SQL, PySpark, Apache Spark, Hive, Trino, Databricks, AWS S3, and Azure. My experience spans production ETL, data migration, parallel-run validation, data reconciliation, and cloud-based data processing across enterprise environments. At GlobalLogic, working with 6sense, I contribute to modernization of production data workloads from Spark 2.4 / Hive 2 to Spark 3.5 / Hive 3 / Trino. My work includes AI-assisted migration workflows using Windsurf, validation of legacy and migrated outputs, Spark-to-S3 workloads using S3A Magic Committer, and integration with a multi-pod data architecture for improved workload isolation and scalability. Previously at IBM, working with Abbott Laboratories, I built production batch ETL pipelines on Azure Databricks using PySpark and SQL, developed ADF-based ingestion workflows, processed 10M+ records using Delta Lake, and implemented data validation and reconciliation frameworks using Medallion Architecture. I enjoy working on data engineering problems involving Spark, ETL, distributed data processing, SQL optimization, cloud data platforms, and production migration workflows. I’m currently focused on growing toward Senior Data Engineer / Big Data Engineer roles where I can contribute to scalable, reliable, and high-performance data platforms.
Work experience
Data Engineer at GlobalLogic, Feb 2026 - Present · 7 mo, Bangalore
Data Engineer at IBM, Nov 2022 - Feb 2026 · 3 yrs 4 mos, Bengaluru, Karnataka, India
