India
With 3+ years starting in data domain and transitioning into data engineering, I've worked on both sides of the data pipeline. I know what analysts need at the end, and I know how to build the infrastructure that gets it to them cleanly and reliably. For the past 1.5 years, my focus has been entirely on data engineering: designing and building ETL/ELT pipelines, cloud data warehouses, and end-to-end data infrastructure on Azure. My core engineering stack includes SQL, Python, PySpark, Azure Data Factory, Snowflake, Databricks, Apache Airflow, and DBT across the full pipeline lifecycle from raw ingestion through transformation, modeling, and delivery. I've delivered across enterprises, client engagements in Supply chain, TRS systems automating manual reporting workflows, building Azure Data Lake-based warehouse solutions, and implementing Customer Data Platform infrastructure using Adobe Experience Platform to unify fragmented customer data into clean, activation-ready profiles for personalization at scale. Strong in Agile delivery, experienced working across both technical and business stakeholders, and comfortable operating in complex, on-premise and cloud-hybrid data environments.