Jay Jung
Software Engineer at Datadog
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolJay Jung is a pragmatic software engineer with three years of professional experience building low-latency, reliable systems and developer-facing platforms. He has shipped backend and database improvements at scale—contributing to Facebook’s RocksDB with features like wide-column entity support and refined rate-limiter logic—and has supported external developer workflows across Facebook’s API and support tooling. At Capital One he focused on real-time big-data retrieval, distributed rate limiting, and cache integrations, and he now continues to work on observability and platform reliability at Datadog. Comfortable across full-stack and infrastructure concerns, Jay pairs hands-on systems work with a developer-support mindset that improves both performance and developer experience. He holds a BS in Computer Science and Bioengineering from the University of Pennsylvania and brings a practical blend of product-focused engineering and open-source contributions.
3 years of coding experience
8 years of employment as a software developer
Bachelor of Science (B.S.) Computer Science Bioengineering, Bachelor of Science (B.S.) Computer Science Bioengineering at University of Pennsylvania
Github Skills (12)
data-structures10
databases10
storage-engine10
c-language10
cprogramming-language10
performance-optimization10
database-design10
data-structure10
database10
concurrency9
algorithms9
filesystem8
Programming languages (1)
Github contributions (4)
facebook/rocksdb
May 2023 - Mar 2025
A library that provides an embeddable, persistent key-value store for fast storage.
Role in this project:
Back-end Developer / Database Engineer
Back-end Developer / Database EngineerContributions:2 releases, 452 reviews, 135 PRs in 1 year 11 months
Contributions summary:Jay primarily contributed to the RocksDB database by implementing and improving core functionalities related to data storage and retrieval. They worked on rate limiter refill logic, refining the database's write performance and fairness. Furthermore, they introduced and expanded support for wide-column entities and related APIs such as `PutEntity` and `GetEntity`, which enhances the database's capabilities for handling structured data. They also implemented the use of the new `WaitForCompact` API and added options such as wait for purge or timeout.
persistent-storagebigtablefast-storagelsm-treedatabase
jaykorean/rocksdb
May 2023 - Mar 2025
A library that provides an embeddable, persistent key-value store for fast storage.
Contributions:700 pushes, 206 branches in 1 year 11 months
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