- Building Clarisights from ground up- Involved with everything tech, solving problems like infrastructure design, data engineering, database design, data science, product development, team building etc.

Working as an official Apache HBase committer. Apache HBase (hbase.apache.org) is an open source real-time, distributed, scalable, sparse big data store in the Hadoop ecosystem, and falls under the NoSQL paradigm of databases.Responsibilities:• Contributing to HBase with new features, bug fixes, code reviews, community participation etc.• Deciding release plans, applying contributors’ patches, monitoring commits and issues, helping users etc.

Worked at part of the HBase team at Facebook (now Meta) architecting, developing, maintaining and deploying HBase at Facebook at a combined scale of a few hundred petabytes.Responsibilities:• Onboarding and driving cross team projects that used HBase at Facebook.• Working closely with teams using HBase at Facebook to enable both latency and throughput sensitive workloads through efficient data modelling, workload distribution and traffic shaping based on use case analysis.• Scaling HBase clusters from scratch to tens of petabytes to drive corresponding use cases• Performing in-depth analysis for architectural, systemic and logical optimizations for squeezing maximum performance from the underlying hardware.• Contributing to Apache HBase with new features and bug fixes aligning HBase roadmap at Facebook.• Tech branding through HBase community interaction including attending and speaking at meetups and conferences.

Worked as a part of Hive (Hive + Hue) team, which was the data warehouse solution at Rocket Fuel while enabling analysts and engineers at RocketFuel to perform large scale analytics on 10s of petabytes of data.• Apache Hive is an open source data warehousing solution and is a part of the Hadoop ecosystem.• Cloudera Hue is a web interface for analyzing data with Hadoop.Responsibilities:• Maintaining Hive and Hue at Rocket Fuel, fixing bugs, implementing wrapper functionalities and researching possible optimizations for better scaling.• Helping Hive users in writing more efficient queries through knowledge delivery and automated optimizations based on internal schema.