Nayanika Upadhyay

San Francisco Bay Area United States

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Summary

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Rockstar

🎓

Top School

Nayanika Upadhyay is a software engineer with 5 years of experience building high-performance distributed systems, in-memory caching, and cloud-ready data platforms across Netflix, Yahoo, and NetApp. She helped scale Netflix’s Hollow-based publish/subscribe and key-value services for versioned datasets and contributed backend fixes and performance improvements to the widely used Netflix/hollow project. Her work at Yahoo included latency-optimizing mailbox caches, HBase schema migrations for millions of users, and rate-limiting and categorization services that reduced operational load. Comfortable in both systems design and hands-on engineering, she has a strong background in storage, SANs, and network-aware simulations from earlier NetApp research. Based in the San Francisco Bay Area with an MS in Computer Science from UC Irvine, she’s focused on Distributed Systems, Big Data, and Cloud Computing and brings a pragmatic, performance-first approach to production systems.

5 years of coding experience

8 years of employment as a software developer

BITS Pilani, Birla Institute of Technology and Science

High School ICSE, High School ICSE at St. Anthony's Junior College

University of California, Irvine

English, Hindi

Github Skills (10)

javas10

api10

apidoc10

java10

performance-optimization9

debug9

debugging9

data-structures8

testing8

data-structure8

Programming languages (2)

JavaGo

Github contributions (4)

Netflix/hollow

Dec 2020 - Nov 2021

Hollow is a java library and toolset for disseminating in-memory datasets from a single producer to many consumers for high performance read-only access.

Role in this project:

Back-end Developer

Contributions:19 releases, 82 reviews, 33 commits in 11 months

Contributions summary:Nayanika primarily focused on back-end development within the Hollow library. Their contributions include fixing compilation errors and addressing NullPointerExceptions (NPEs) in core components like `StaleHollowReferenceDetector` and `HollowDiffMatcher`. They added new features to the `AnnouncementListener` API, including supporting read states. Additionally, the user improved UniqueKeyIndex performance and addressed various code style violations.

memoryjava-librarydatasetbig-dataconsumers

nayanika-u/pinot

Mar 2025 - Mar 2025

Apache Pinot - A realtime distributed OLAP datastore

Contributions:12 pushes, 8 branches in 22 days

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