Summary
Gaurav Saxena is a Principal Engineer based in the San Francisco Bay Area with 11 years of experience designing learned, self-optimizing distributed data systems such as Amazon Redshift and DynamoDB. He specializes in query processing, storage layers, and autonomic database techniques that use ML to adapt to workload patterns, and he presented these ideas at re:Invent 2018. His background spans production-critical distributed replication, automatic admin tooling for Zookeeper, and building high-performance in-memory analytics stores that handled large clickstream and sensor datasets. An active open-source maintainer and committer, he leads projects from Java collection implementations to distributed in-memory stores and browser prototyping tools. Combining academic research in view maintenance and query compilation from UCSD with hands-on AWS engineering, he brings both theoretical rigor and practical, production-grade delivery to complex data infrastructure problems.
11 years of coding experience
9 years of employment as a software developer
Indian Institute of Technology Madras
University of California, San Diego
English, Hindi