Eric Hwang is a Staff Software Engineer in San Francisco with a decade of experience helping teams build reliable web applications, currently focused on framework engineering at Lever to improve developer experience and productivity. He spent five years at Google driving large-scale front-end efforts for the AdWords webapp—leading accessibility and visual refreshes, shipping Dynamic Search Ads and an experiments UI, and creating a pre-submit linter used by 10+ teams. His background spans full‑stack product work and notable open-source contributions to realtime collaboration stacks (ShareDB, Racer, Derby) and TypeScript typings in DefinitelyTyped, showing deep backend, tooling, and API design expertise. A pragmatic mentor and code-quality advocate (100+ interviews and multiple interns mentored), he pairs an EECS education from Olin with a track record of improving both developer workflows and end-user products.
10 years of coding experience
8 years of employment as a software developer
BS, Electrical and Computer Engineering (EECS), BS, Electrical and Computer Engineering (EECS) at Franklin W. Olin College of Engineering
Realtime database backend based on Operational Transformation (OT)
Role in this project:
Back-end Developer
Contributions:26 releases, 131 reviews, 100 commits in 5 years 1 month
Contributions summary:Eric primarily contributed to the backend of the ShareDB project, focusing on improving the database functionality. Their work involved resolving a circular dependency, adding tests for memory leaks in document subscriptions, and enhancing the "readSnapshots" middleware by adding context information to facilitate more flexible usage. Furthermore, the user made code review changes to the "readSnapshots" middleware, demonstrating a focus on code quality and maintainability. These contributions support ShareDB's role as a real-time database backend.
Contributions:21 releases, 31 reviews, 64 commits in 7 years 9 months
Contributions summary:Eric primarily focused on enhancing the core functionality of the Racer engine. Their contributions involved refactoring the query system to handle duplicate IDs and improve the efficiency of data management. Furthermore, the user addressed callback handling within the subscription process and optimized the internal data structures for better performance. These changes collectively aimed to improve the robustness and reliability of the Racer engine.
realtimesynchronizationnode-jsjavascriptnodejs
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