Python Developer

Developed a document storage API (Django REST Framework) for user KYC and profile images with GCS signed URLs and CDN access, cutting retrieval time by 70%. Optimized API performance via MIME-type detection and schema validation, increasing upload success rate. Designed and deployed a Kafka-to-S3 ingestion pipeline processing 1M+ log events daily with Parquet compression and partitioning, improving Athena query performance by 40%. Implemented Kafka null-event based auto-flush triggers reducing in-memory buffer time from 10 minutes to under 2 minutes, ensuring reliable event delivery.

Built region and CMS filters to streamline search management. Split wallet balance into Fleet Balance, enhancing scalability and maintainability. Optimized API performance using config-layer caching of connector metadata with Spring beans, reducing database load. Developed S3-based attachment upload flow for ticket management system with file validation and dynamic URL generation.

Architected and led the development of a real-time user segmentation engine that processes 40M+ frontend events and 30K+ transactional events daily maintaining accurate behavioral lifecycle stages (C0 ,L1 ,L2 etc) for ∼6 lakh monthly active users across 7 product verticals. Built a configurable recursive rule engine, enabling product and growth teams to define and modify user journey progression via JSON configs without code changes or deployments. Engineered an Elasticsearch sync service consuming 50K+ Kafka events per batch and indexing documents with dynamic time-based indices, enabling sub-second search latency for time-series analytics. Reduced database load by replacing unconditional stage lookups on every event with targeted queries — cut daily MySQL reads from ∼3.8M to under 900K (∼ 91% reduction), dropping peak QPS from ∼50K to ∼5K. Collaborated with DevOps to migrate Debezium Kafka Connectors to Kubernetes, writing Deployment, Service, ConfigMap, and Secret manifests, reducing maintenance downtime by 80%. Developed REST APIs for Kafka Connectors, enabling self-serve management of Debezium connectors without manual Kafka cluster access.