Shrinand Thakkar
Senior Software Engineer at linkedin
Summary
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SeniorShrinand Thakkar is a Senior Software Engineer based in Sunnyvale with 5 years of experience building large-scale, real-time streaming systems using Kafka and AWS. At LinkedIn he contributes to Brooklin, an extensible distributed system for reliable nearline data streaming, focusing on backend reliability, task management, and observability improvements. Previously at Grab he helped operate a managed Kafka platform and a stream-processing framework that handled over 300 billion events per week, designing durable APIs, schema contracts, and monitoring tooling. He holds an MS in Computer Science from Stony Brook and a strong engineering foundation from G H Patel College, combining academic rigor with hands-on production experience. Notably, he blends deep operational expertise with a pragmatic focus on observability and task lifecycle correctness in distributed stream processing.
5 years of coding experience
Github Skills (10)
data-streaming10
zookeeper10
java9
debug9
distributed-systems9
debugging9
javas9
kafka8
test-automation8
change-data-capture7
Programming languages (1)
Github contributions (2)
linkedin/brooklin
Apr 2021 - Jun 2022
An extensible distributed system for reliable nearline data streaming at scale
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 192 reviews, 13 commits in 1 year 1 month
Contributions summary:Shrinand primarily contributed to the back-end aspects of the data streaming system, with a focus on improving the reliability and functionality of the system. They implemented features such as adding hostnames to ZooKeeper connector paths and refactoring stopping tasks on assignment changes. The user also worked on improving logging for partition assignments and improving task management. Their work involved modifying core components related to task management and data streaming.
complex-event-processingstreamingdistributed-systemsextensiblescalability
shrinandthakkar/brooklin
Apr 2021 - Oct 2023
An extensible distributed system for reliable nearline data streaming at scale
Contributions:97 pushes, 36 branches in 2 years 7 months
stream-processingaccumulostreaming-datacomplex-event-processingdistributed-system
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