Frank Hu
Engineering Manager Data Platform
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolFrank Hu is an engineering manager specializing in data platforms with 11 years of experience building high-performance, byte-efficient OLAP systems from startups to large-scale product teams. Based in San Francisco, he currently leads Data Platform engineering at TikTok after architecting real-time streaming pipelines and a distributed query engine at Optimizely that processed billions of events and petabytes of data. He combines hands-on systems work—contributing performance and Parquet support improvements to the widely used Presto project—with product-driven leadership, having co-founded MailTime and shipped an App Store–featured iOS product. Frank has deep expertise across Kafka, Samza, HBase, Presto, Parquet and Airflow, and has operationalized encryption-at-rest for petabyte-scale data. He is as comfortable optimizing compilers and memory management for query engines as he is scaling microservices and real-time analytics for customer-facing use cases. His background in research and UAV vision systems hints at a pragmatic curiosity that drives novel, cross-disciplinary solutions.
11 years of coding experience
4 years of employment as a software developer
Exchange Student, Computer Science, Exchange Student, Computer Science at Dartmouth CollegeThe Chinese University of Hong Kong (CUHK)
English, Chinese, Chinese
Github Skills (10)
javas10
big-data10
presto10
sql10
java10
testing9
parquet9
query-optimization9
data-engineering8
hadoop8
Programming languages (7)
Github contributions (5)
prestodb/presto
Jun 2020 - Apr 2021
The official home of the Presto distributed SQL query engine for big data
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 reviews, 2 commits, 14 PRs in 10 months
Contributions summary:Frank contributed to the Presto distributed SQL query engine by optimizing common sub-expression handling within the `CursorProcessorCompiler`, improving query performance. Further contributions involved fixing memory management and data size calculations, ensuring data consistency. The user also enabled Parquet format support for TPC-H and TPC-DS tests, and addressed test flakiness. Finally, the user added TPC-DS test queries for Q2 and Q78 and disabled Q64.
distributed-sqlquerybigdataquery-enginesql
frankobe/presto
Apr 2021 - Jul 2023
The official home of the Presto distributed SQL query engine for big data
Contributions:58 pushes, 14 branches in 2 years 2 months
queryhivebigdataquery-enginesql
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