India's largest online grocery platform. Pioneered the monolith-to-microservice transition, built cross-database reporting at scale, and led data pipeline engineering for customer recommendations.
Designed and developed Stitch, enabling cross-database join operations across MySQL, PostgreSQL, MS SQL, Redshift, and Athena — processing 20,000+ reports daily.
Business data lived across 5+ database systems with no way to join or query across them. Teams relied on manual data extraction and Excel analysis.
Built a query federation layer that could join across MySQL, PostgreSQL, MS SQL, Redshift, and Athena, with scheduled report generation and distribution.
Processes 20,000+ reports daily, providing critical business metrics and improving operational efficiency for hubs and darkstores.
Led a team of 5 data scientists and engineers in building a data pipeline processing 3 million+ order items daily for customer basket-building recommendations.
Recommendation data was stale and processing was slow, limiting the ability to personalize customer baskets effectively.
Airflow-orchestrated pipeline using pandas and Apache Spark, processing 3M+ order items daily to deliver transformed data for the recommendation engine.
Enabled real-time basket-building recommendations. Also contributed to MBQ service that reduced perishable waste by 40% and achieved 95% availability for 5,000+ SKUs.
Pioneered BigBasket's microservices transition, re-architecting core member APIs and improving performance by 64% in latency for login, sign-up, and address management.
Monolithic architecture with tightly coupled domains, slow deployments, and cascading failures affecting all customer-facing features.
Extracted core member APIs (login, sign-up, address) into independent services, with proper API contracts and independent deployment pipelines.
64% latency reduction for core member operations. Established the pattern for subsequent service extractions across BigBasket.