Jianfeng Zhang is a Senior AI Engineer and seasoned Data & AI architect with 15+ years building large-scale data infrastructures, knowledge graphs, and generative-AI integrations for enterprises. He has driven AI-driven metadata platforms and LLM-based automation at scale—designing a graph-backed enterprise metadata knowledge graph and BI copilot that served thousands of users and thousands of Spark/Flink pipelines. An active Apache PMC member and long-time committer (Zeppelin, Tez, Livy, Pig), he blends deep open-source leadership with pragmatic product delivery, including contributions to Apache Doris and its Flink connector. His work spans backend systems, front-end documentation and UI improvements, and practical API redesigns (e.g., HTTP RESTful APIs for Doris), reflecting full-stack fluency. Based in Shanghai, he combines academic pedigree from Fudan and Zhejiang with a track record of translating tribal knowledge into structured AI assets via LLM agents. He is now focused on bridging legacy data systems to next-generation AI applications in production.
11 years of coding experience
17 years of employment as a software developer
Master Computer Science, Master Computer Science at Fudan University
Bachelor Computer Science, Bachelor Computer Science at Zhejiang University
Contributions:57 reviews, 308 commits, 170 PRs in 10 months
Contributions summary:Jianfeng primarily contributed to the website's documentation and user interface. They added documentation for new features and release notes, enhancing the website's content and providing information to users. Furthermore, they worked on the website's front-end, modifying the download page and site map pages, which involved changes to React components and potentially some styling adjustments.
Apache Doris is an easy-to-use, high performance and unified analytics database.
Role in this project:
Back-end Developer
Contributions:1061 reviews, 237 commits, 642 PRs in 2 years 7 months
Contributions summary:Jianfeng contributed to the Apache Doris project by implementing new HTTP RESTful APIs for the Frontend using Spring MVC, replacing the original Netty-based implementation. Their work involved creating new packages and modifying existing code related to hardware information, including integrating with the Oshi library. Additionally, they addressed bugs in the Spark Doris connector, specifically fixing issues related to HTTP v2 authentication and data format inconsistencies, as well as enabling http v2. The user also supported the implementation of export functionalities and added the ability to specify certain columns to be exported.
dbmsapache-dorisdbtreal-timehudi
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