Bryan Ji is a Staff Software Engineer at LinkedIn with eight years of experience building large-scale data infrastructure focused on privacy, governance, and compliance. He has driven end-to-end data lifecycle work—from orchestration and retention to visualization—while navigating regulatory regimes like GDPR, the DMA, and the AI Act. Bryan pairs hands-on backend engineering with open-source contributions to high-performance systems such as Apache Pinot, where he improved anomaly detection caching and secure certificate-based auth. Based in San Francisco, he blends deep technical expertise in compute engines and databases with practical privacy engineering, and he’s known for turning compliance requirements into efficient, production-ready systems.
Apache Pinot - A realtime distributed OLAP datastore
Role in this project:
Backend Developer
Contributions:8 commits, 11 PRs, 86 comments in 2 months
Contributions summary:Bryan primarily contributed to the backend infrastructure of the Apache Pinot project, focusing on improvements to the Thirdeye anomaly detection module. Their work involved implementing a centralized cache for anomaly detection using Couchbase, including adding support for certificate-based authentication and refactoring the caching DAO. They also addressed logging issues and optimized data prefetching in dimension exploration jobs, enhancing the performance and efficiency of the system. Furthermore, they added relevant documentation related to the centralized caching functionality.
Contributions:51 commits, 44 pushes, 2 branches in 7 months
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