At AU Small Finance Bank, I design and maintain PySpark pipelines on a Databricks Delta Lake Lakehouse, turning more than 100 million banking records into analytics-ready data. I tuned Spark jobs to cut processing time by 30–45 minutes per run.
I built AWS Lambda triggers that send action-based customer alerts to the RM application, lifting application utilization by 10–20%. I also model financial and customer data for reporting and business KPIs.
I led the Fincare-to-AU Bank warehouse migration, standardizing and reconciling data from more than 15 source systems. I independently designed a PySpark framework for PostgreSQL-to-Redshift migration that reduced infrastructure costs by 30%.
I maintain Airflow DAGs with retries and SLA-based alerting, and protect sensitive financial data with access controls, PII masking, and row-level security. Earlier, as a Data Engineer Intern at AU Small Finance Bank, I supported production ETL/ELT pipelines and integrated REST APIs with Spark and MySQL.
