Jul 2024 – Present · 1 yr 11 mos · Remote

• Working with the Food Search Team
• 1. Led the migration from Elasticsearch 7.x to OpenSearch 2.17, achieving a projected 25% reduction in infrastructure costs and 8% lower storage usage by cleaning up unused fields and optimizing cluster configurations.
• 2. Streamlined AWS Batch cron infrastructure by merging redundant jobs, reducing two Deployable Units (DUs) and improving overall job execution time by 20%, leading to lower operational costs.
• 3. Implemented Redis caching within a microservice, reducing traffic to Elasticsearch by ~20% and cutting unnecessary query costs.
• 4. Optimized application logging across core services, reducing log ingestion volume from 10 MB/min to 1 MB/min and decreasing error logs by 60%, improving observability and reducing log storage costs.
• 5. Consolidated multiple GripMock containers used for Java downstream services into a single container, simplifying the Docker Compose setup and reducing CI pipeline execution time by ~9%, improving developer productivity and pipeline efficiency.
• 6. Designed and implemented real-time data ingestion pipelines into Elasticsearch, triggered by Kafka events, to enhance user experience with fresher and more relevant search results.
• 7. Built Grafana dashboards for key backend services to enable real-time monitoring and efficient on-call debugging, contributing to improved service reliability and faster incident response.
• 8. Helped improve search retrieval relevancy benefitting mostly Restaurants which might not be popular overall but have specialized popularity for certain dishes/cuisines . This helped 36p iUE gain at a platform level and reduce null searches by 6 bip and get visibility for Restaurants.
• 9. Part of one Extra off project from search side and handling facet logic shown to user.