Maytas Monsereenusorn
Staff Software Engineer (L6) at Netflix
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMaytas Monsereenusorn is a Staff Software Engineer at Netflix with six years of hands-on experience building backend systems for large-scale data platforms. He focuses on big data compute engines and has advanced from Senior to Staff within Netflix after earlier roles at Imply, Amplitude, Apple, and AppDynamics. An active open-source committer and PMC member on Apache Druid, he contributed a robust ANY aggregator and related fixes that improve real-time analytics for numerical and string types while handling nulls and edge cases. He combines a Berkeley double major in Computer Science and Economics with practical expertise shipping production data pipelines and core engine changes, making him equally comfortable in design, performance tuning, and test-driven delivery. Notably, his contributions reflect depth in core database internals rather than surface tooling, helping power high-throughput analytics workloads.
6 years of coding experience
6 years of employment as a software developer
Bachelor of Arts (B.A.), Computer Science and Economics (Double Major), Bachelor of Arts (B.A.), Computer Science and Economics (Double Major) at University of California, Berkeley
English, Thai
Stackoverflow
101reputation
10kreached
4answers
2questions
Github Skills (20)
aggregate10
aggregator10
testing10
apache-druid10
java10
ag10
javas10
aggregations10
aggregates10
software-quality9
sql9
performance-optimization8
parse-platform6
swift6
xcode6
Programming languages (4)
Github contributions (5)
apache/druid
Jan 2020 - Jan 2023
Apache Druid: a high performance real-time analytics database.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:605 reviews, 133 commits, 292 PRs in 3 years
Contributions summary:Maytas implemented and tested a new ANY aggregator in Apache Druid, contributing to its real-time analytics capabilities. Their work involved adding functionality to aggregate any values, including numerical and string columns, and ensuring correct behavior with null values. The user also addressed code quality issues, added documentation, and wrote unit tests to ensure the stability and correctness of the new feature. Furthermore, the user fixed issues with other related aggregator implementations like latest/earliest, adding test cases.
real-timebig-datadruiddatabasehadoop
maytasm/druid
Jan 2020 - Apr 2025
Apache Druid: a high performance real-time analytics database.
Contributions:4 PRs, 750 pushes, 249 branches in 5 years 3 months
real-time-analyticsanalyticssqlapachebig-data
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