Gunj Desai

Core dev in building pipelines for parsing Ethererum data. • Spark job for parsing events, transactions and traces data in Ethereum while checking for ABI mismatches and error handling of missing rows with ability to parse data in real time.This job can run through all evts generated on the Ethereum blockchain with 5 hrs and process every single record,the approximate size of which is 3.9TB. • Designed a system to breakdown ABI’s on a topic & event signature level, so that dups can be avoided in storing ABI

Core Contributor and maintainer for Video Recommendation Platform which aggregates data In near real-time and building A.C.I.D capabilities on S3 • Created smart aggregates across 20 categories which improved recommendations and increased engage time significantly • Built a near realtime analytics platform on Apache H.U.D.I + Debezium + Apache Kafka which runs multiple pipelines consisting of 100+ tables and has a latency of 45 seconds max with simple transformations included

Responsible for creating a Near Real Time Aggregation Platform that returns personalised user payment options under 100ms • Created smart aggregates across 6 categories which improved conversions significantly • Revamped Events Platform that generates about 1TB of data per day and reduced errors by 40% • Setting up an OLAP Store which is designed to ingest petabytes of data and respond with sub second responses • Building an Event Stitching Platform for merging events for different micro- services

Responsible for creating BookMyShow’s Big Data and Clickstream Platform and its PWA Ticketing Platform • Created a Clickstream platform for all the platforms which ingests more the 2 million events every 5 minutes • Increased conversions of mobile web by 80%. • Initial load time on 2G network is 3.1 seconds (along with smart personalisation also calculations) Brought down subsequent load time of the Web down to 1.9s • Moving PZN Apis to new Akka Stack from legacy stack