Dian Qi
研发工程师 at 阿里云计算有限公司
Haidian District, Beijing, China
Summary
👤
Senior🎓
Top SchoolDian Qi is a senior research and development engineer with 8 years’ experience building large-scale data platforms and real-time lakehouse pipelines, currently driving storage and pipeline features for AnalyticDB at Alibaba Cloud. He combines strong academic foundations—a dual B.S. in Computer Science and Applied Math from UCSD—with hands-on systems work from IBM research to production services, including causal-inference research and a granted patent submission. An active open-source contributor, Dian has implemented schema-change and multi-table write support for Apache Paimon and contributed to Flink CDC and Apache Hudi, improving streaming-to-batch interoperability for real-time analytics. Previously he led architecture rewrites and backend/data-schema redesigns for high-scale K-12 edtech products, decoupling legacy Drupal systems and introducing containerized developer workflows. Equally comfortable in low-level storage/protocol work and product-facing engineering, he brings a pragmatic blend of research rigor and production-focused delivery.
8 years of coding experience
理科, Science, 4.0, 理科, Science, 4.0 at 中国人民大学附属中学（人大附中）Bachelor's degree, B.S. in Computer Science and B.S. in Mathematics (Applied), 3.97/4.0, Bachelor's degree, B.S. in Computer Science and B.S. in Mathematics (Applied), 3.97/4.0 at 美国加州大学圣迭戈分校
Github Skills (11)
javas10
big-data10
flink-sql10
spark10
data-lake10
apache-flink10
java10
data-engineering10
testing9
data-ingestion8
sql8
Programming languages (11)
Github contributions (5)
apache/paimon
Apr 2023 - Jul 2023
Apache Paimon is a lake format that enables building a Realtime Lakehouse Architecture with Flink and Spark for both streaming and batch operations.
Role in this project:
Back-end Developer / Data Engineer
Back-end Developer / Data EngineerContributions:13 reviews, 11 PRs, 30 comments in 3 months
Contributions summary:Dian contributed to the Apache Paimon project by implementing and testing features related to schema changes in Flink. They fixed a manifest list naming issue and added support for a multi-table write operator within the Flink framework. The user's work included modifying core components and developing tests, demonstrating a focus on improving data lake functionality for streaming and batch operations.
flinkdistributed-systemsubprojectapachebig-data
qidian99/Gitbook
Jun 2020 - May 2021
Contributions:203 pushes, 1 branch in 11 months
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