Jonathan Gao
Software Engineer IV at Databricks
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJonathan Gao is a Software Engineer IV with nine years of experience building scalable data and distributed systems, currently focused on data ingestion at Databricks after contributing to DynamoDB replication and log services at AWS. He blends a ground-up understanding of hardware and microprocessors from an ECE background with MEng-level software craftsmanship from Cornell, enabling him to bridge firmware, backend, and cloud infrastructure work. Jonathan is passionate about databases and storage systems and has contributed performance and correctness improvements to the widely used Apache DataFusion SQL engine. Known for optimizing query planners and hardening edge-case behavior (e.g., NULL handling and expression simplification), he brings both pragmatic bug fixes and optimizer-level enhancements. Early hands-on projects—ranging from PCB design and hardware test frameworks to full-stack web and devtooling—reflect a rare full-stack-to-silicon breadth. Based in Seattle, he combines systems-level rigor with a continual curiosity for learning and improving complex data platforms.
9 years of coding experience
5 years of employment as a software developer
Great Neck North High SchoolMaster of Engineering - MEng Computer Science, Master of Engineering - MEng Computer Science at Cornell University
Chinese, English, French
Stackoverflow
629reputation
84kreached
44answers
5questions
azure
top-5%
Github Skills (17)
query-optimization10
fusion10
sql10
query-engine10
rust10
azure9
algorithm7
algorithms7
data-structure7
data-structures7
powershell6
hive6
azure-powershell6
hadoop-streaming6
powershell-cmdlets6
Programming languages (6)
Github contributions (5)
apache/datafusion
Aug 2022 - Dec 2022
Apache DataFusion SQL Query Engine
Role in this project:
Backend Developer
Backend DeveloperContributions:552 reviews, 2 commits, 251 PRs in 3 months
Contributions summary:Jonathan contributed to the Apache DataFusion project by implementing and optimizing SQL query engine features. Their work includes fixing bugs related to case evaluations with NULLs and improving the handling of expressions like `IS NOT NULL` and `IS NULL`. The user also focused on enhancing the query optimizer, such as by simplifying expressions and removing unnecessary simplification rules, improving the overall efficiency of the query engine. They made various code changes to enhance the performance and correctness of the DataFusion query engine.
querypythonquery-enginedataframerust
jonahgao/btree
Jan 2017 - Oct 2018
Contributions:32 commits, 4 pushes in 1 year 9 months
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