sauradip.sengupta

Cloud Migration : Migrated 300+ credit fraud detection variables from a legacy monolith to a microservices-based system enabling real-time feature availability for XGBoost ML models improving model readiness time by 40%. ◦ Optimized business logic: Optimized legacy variables logic by implementing bucketing and transformation techniques to enable faster real-time computation and improve efficiency for downstream data consumption and analytics. ◦ ETL Pipeline Engineering: Accelerated data extraction, transformation, and cost optimization by engineering automated incremental data loading workflows using a highly configurable, data-driven approach , reducing pipeline runtime by 55% and cloud costs by 20% through efficient SQL queries, CTEs, indexing, and partitioning strategies. ◦ Data Integrity Validation Framework: Developed a scheduled PySpark pipeline for weekly match rate analysis between migrated and legacy datasets, integrating alerting mechanisms to automatically flag data drift and inconsistencies, ensuring proactive data integrity.

◦ Test case migration : Migrated test cases from the TestNG framework to Cucumber, enabling a shift from TDD to BDD. This transformation led to improved performance, enhanced readability, and better collaboration between QA and developers. ◦ Dependency Management : Addressed dependency mismatches across multiple microservices, leveraging Maven to update and align dependencies. It reduced system vulnerabilities and ensured seamless integration between services ◦ Bug Resolution : Actively worked on and resolved numerous bug tickets across the codebase, contributing to improved product stability and faster sprint velocity.