Manoj Govindassamy - Lead at Cohere

Manoj Govindassamy

Lead at Cohere

San Francisco Bay Area United States

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Summary

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Rockstar

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Top School

Manoj Govindassamy is a seasoned systems and distributed-systems engineer with 9 years of documented experience in the San Francisco Bay Area and a long career building resilient storage and infrastructure software. He currently leads engineering at Cohere after staff-engineer roles focused on autonomy at Waymo and Argo AI, and earlier deep work on HDFS and scale-out storage at Cloudera and Nimble Storage. Manoj’s open-source contributions to Apache Hadoop and Apache Hudi show practical expertise in HDFS snapshot consistency, datanode maintenance, and metadata-table performance—improvements that target operational stability and large-scale data integrity. He has a strong track record designing fault-tolerant algorithms, non-disruptive upgrades, and high-performance control planes for storage systems. Colleagues describe him as the kind of engineer who blends low-level storage plumbing with production-focused optimizations, able to both diagnose tricky consistency bugs and ship system-level features. Trained in information technology at Pondicherry Engineering College, he combines academic roots with years of hands-on production reliability work.

9 years of coding experience

16 years of employment as a software developer

Bachelor of Technology - BTech Information Technology, Bachelor of Technology - BTech Information Technology at pondicherry engg. college

Github Skills (11)

javas10

big-data10

hdfs10

apache-hudi10

java10

snapshots10

data-engineering10

filesystem9

distributed-systems9

data-storage9

testing8

Programming languages (1)

Java

Github contributions (5)

apache/hudi

Oct 2021 - Mar 2022

Upserts, Deletes And Incremental Processing on Big Data.

Role in this project:

Back-end Developer

Contributions:368 reviews, 40 commits, 43 PRs in 4 months

Contributions summary:Manoj's contributions focused on improving the Hudi metadata table's performance and features. They implemented changes to optimize the metadata table compaction process, specifically adjusting parameters to trigger compaction more efficiently. The user also addressed potential performance bottlenecks in the BitCaskDiskMap, preventing hostname resolution in logging and re-estimating payload size calculations. Additionally, they added features to improve metadata table support for various operations, including rolling back commits and incorporating virtual keys to reduce storage overhead.

stream-processingbigdatahudiincrementalapacheflink

apache/hadoop

Aug 2017 - Jan 2018

Apache Hadoop

Role in this project:

Back-end Developer

Contributions:23 commits in 5 months

Contributions summary:Manoj primarily worked on the Apache Hadoop project, specifically addressing issues related to HDFS snapshots and datanode administration. Their contributions include bug fixes, such as resolving issues with open files during snapshot deletion and ensuring consistency during file truncation and append operations. The user also added features like enhanced dfsadmin reports and implemented code for datanode maintenance state, indicating a focus on improving HDFS stability, data integrity, and operational efficiency.

apachebig-datasparkhadoopjava

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