Sanket N
Senior Software Engineer at LinkedIn
California, United States
Summary
🤩
Rockstar🎓
Top SchoolSanketh Nalli is a Senior Software Engineer with 14 years of experience building robust distributed systems and data platforms, currently focusing on data privacy and secure data processing at LinkedIn. He has deep backend expertise from contributions to high-scale projects like Ambry, where he improved metadata caching, non-blocking routing, and performance observability for a distributed object store. Prior roles at AWS (DynamoDB, Redshift) and Oracle involved designing replication protocols, cluster managers, and parallel execution strategies that preserve data integrity across clusters. His background includes research-grade work on NVM filesystems and low-latency metadata lookups, reflecting a mix of systems research and production engineering. Based in California, he combines pragmatic engineering with attention to observability and performance in critical paths. He brings a proven track record of turning complex distributed-systems problems into measurable, test-covered solutions.
14 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Computer Sciences, Master of Science - MS, Computer Sciences at University of Wisconsin-MadisonBachelor's degree, Information Technology, Bachelor's degree, Information Technology at National Institute of Technology Karnataka
Japanese
Github Skills (11)
javas10
caching10
object-storage10
performance-optimization10
java10
metric9
unit-testing9
rest-api8
api-rest8
restful-api8
api-design8
Programming languages (4)
Github contributions (5)
linkedin/ambry
May 2022 - Jan 2023
Distributed object store
Role in this project:
Back-end Developer
Back-end DeveloperContributions:893 reviews, 47 commits, 345 PRs in 7 months
Contributions summary:Sanket primarily contributed to the backend functionality of the Ambry object store. Their work involved modifying code related to metadata caching, specifically for composite blobs, and integrating the cache within the non-blocking router. They also addressed performance issues by removing or reducing logging in critical paths and refactoring code to improve efficiency. Furthermore, the user added metrics and unit tests to evaluate the cache's performance and reliability.
osgidistributed-systemsobject-storedistributed-object-storejava
snalli/mnemosyne-gcc
May 2016 - Oct 2018
GCC port of TM system Mnemosyne
Contributions:31 commits, 4 PRs, 60 pushes in 2 years 5 months
gcc
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