About
Staff-level backend engineer with 9 years building distributed systems, cloud-native infrastructure, and microservices at scale. At LinkedIn, led technical architecture for Darwin platform: Kubernetes-native systems, production backend services, and high-throughput streaming pipelines. At Flipkart, built and scaled backend systems for high-stakes financial flows: ad budgeting pipelines, invoicing automation, and data infrastructure across multiple DCs, while owning performance engineering at Big Billion Day scale. Comfortable driving roadmap and system design decisions independently in ambiguous, fast-moving environments.
Kubernetes-native Jupyter platforms, semantic search on notebooks (Kafka + Qdrant + GPU embeddings, P99 < 500ms), K8s pod templatization framework, vertical kernel architecture, and agentic Flink pipeline automation.
Streaming pipelines for ad budget calculations (Kafka + Storm), batch ingestion across DCs, Big Billion Day 2021 scaling — GC tuning, memory optimizations, and red-line traffic testing.
CDC pipelines from MySQL to Elasticsearch, database sharding for BBD 2019, and a warehouse onboarding automation framework that cut SLA from ~10 days to ~1–2 hours.
Backend test scenarios in Node.js, content analytics with Redshift and Kibana, admin tooling in Backbone.js and Ruby on Rails.