Ammar Khaku is a Staff Software Engineer with 14 years of experience building resilient, scalable data platforms at Netflix and Evernote, now focused on Data Platform Engineering in South San Francisco. He combines deep backend expertise in Java and distributed systems with hands-on experience in cloud-native architectures, microservices, and task queues. His open-source contributions include robustness and schema-handling improvements to the widely used Apache Cassandra Java driver and performance-focused work on Netflix’s Hollow, reflecting attention to stability and memory-conscious design. At Evernote he led cross-team data-model redesigns and built production services—from shard-copying microservices to an email templating system—that reduced developer friction and improved reliability. Known for turning complex operational failure modes into pragmatic, horizontally scalable solutions, he pairs strong technical execution with clear documentation and cross-team leadership. Outside core platform work he has a practical knack for bridging legacy APIs and modern runtimes, evidenced by SDK and thrift-stub migrations early in his career.
14 years of coding experience
11 years of employment as a software developer
BS, Mechanical Engineering and Computer Science, BS, Mechanical Engineering and Computer Science at Tufts University
Contributions:48 commits, 20 PRs, 24 pushes in 9 months
Contributions summary:Ammar's commits primarily involve updating generated thrift stubs within the `evernote-sdk-js` repository. These updates include modifications to the `NoteStore.js`, `UserStore.js`, and related files, focusing on the structure and function calls within the Evernote API. The changes reflect a migration from asynchronous JavaScript interfaces to Node.js (CommonJS) interfaces. The commit history reveals a consistent effort in aligning the JavaScript SDK with the underlying Thrift definitions, highlighting the user's involvement in maintaining and updating the core interaction logic of the SDK.
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, 32 reviews, 154 commits in 2 years 11 months
Contributions summary:Ammar primarily focused on refactoring and enhancing the `HollowRecordJsonStringifier` within the `netflix/hollow` repository. They added functionality to allow passing a custom `Writer` to handle potential memory issues. The user also made modifications to the Hollow Explorer UI, exposing the Writer to the page classes to utilize the updated `HollowStringifier`. Furthermore, they improved the data display by correctly representing null nodes in the diff/history UI.
memoryjava-librarydatasetbig-dataconsumers
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