Designed and managed enterprise Elastic Cloud clusters (Azure) with billions of documents and high QPS workloads powering search and analytics.
Implemented ILM policies, shard allocation, rollover strategies, and snapshot/restore processes — cutting query latency by 40% and reducing infrastructure costs
performance by 30%.
Drove cloud cost optimization strategies (capacity planning, auto-scaling, right-sizing), saving millions in annual spend while improving reliability.
Built and optimized SQL stored procedures, indexing, partitioning, and purge automation — increasing data efficiency and compliance.
Engineered real-time data pipelines with Kafka + Databricks for instant ingestion and analytics across multiple business units.
Developed observability dashboards (Kibana + Datadog) for anomaly detection, alerting, and root-cause analysis, ensuring 24/7 uptime of mission-critical systems.
Partnered with SRE, infra, and product teams to establish Elastic governance, query design standards, and scaling policies aligned with business growth.
Engineered real time data pipelines with Kafka and Databricks for near instant ingestion and analytics across multiple business units
Developed observability with Kibana and Datadog for anomaly detection alerting and root cause analysis maintaining around the clock uptime of mission critical systems
Partnered with platform infrastructure and product teams to establish Elastic governance query design standards and scaling policies aligned with business growth
Senior Big Data/Elasticsearch Engineer
United Airlines
Houston, TX
10.2018 - 11.2019
Managed and optimized Kafka & Elasticsearch clusters for large-scale ingestion pipelines supporting global airline operations.
Delivered a 35% reduction in query latency by tuning index mappings, analyzers, and search query design
Executed Elasticsearch cluster migration and scaling strategies with zero downtime, improving search reliability
Designed and implemented Spark/Scala workflows for streaming data, improving pipeline throughput by 40%.
Built real-time Kibana dashboards for operational monitoring, reducing issue detection time from hours to minutes.
Partnered with engineering teams to architect fault-tolerant ingestion and search systems for flight data and customer insights.
Big Data Engineer
84.51
Remote, OH
08.2017 - 10.2018
Collaborated on ETL (Extract, Transform, Load) tasks, maintaining data integrity and verifying pipeline stability.
Implemented randomized sampling techniques for optimized surveys.
Devised and deployed predictive models using machine learning algorithms to drive business decisions.
Compiled, cleaned and manipulated data for proper handling.
Architected real-time ingestion pipelines using Kafka + Spark to support instant retail transaction processing and analytics.
Designed data lake strategies with AWS S3 and Hive, ensuring cost-efficient storage and high query performance.
Automated end-to-end ETL workflows, reducing data availability time from hours to near real-time.
Database Developer
LiquidHub
Bengaluru, India
04.2012 - 11.2015
Conducted tests to identify issues and make necessary modifications.
Developed and optimized SQL stored procedures, triggers, and ETL pipelines for enterprise-scale transactional systems.
Implemented query tuning, indexing, and partitioning strategies, improving reporting performance by 50%+.
Built automated purge and archival processes for high-volume transactional datasets, ensuring compliance and storage efficiency.
Created UNIX shell scripts to automate recurring maintenance, backups, and reporting tasks.
Partnered with analysts and business teams to deliver data-driven reporting solutions on tight deadlines.