Bo Gao
Sr. Software Engineer at Databricks
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolBo Gao is a senior software engineer based in Seattle with 6+ years of experience building distributed systems and cloud-native services, currently advancing streaming engine capabilities at Databricks. He brings deep AWS expertise from six years at AWS where he led cross-organizational projects, shipped device inventory and Snow device platform improvements, and served as a technical mentor and SME. Skilled in both SQL and NoSQL, REST API design, and serverless services like Lambda and DynamoDB, Bo couples pragmatic engineering with a focus on scalability and operational excellence. He is also an active contributor to Apache Spark, enhancing Spark Connect’s Python APIs and stateful streaming features for real-time processing. His background in electrical and computer engineering gives him a systems-oriented perspective that informs both low-level reliability work and high-level architecture decisions.
3 years of coding experience
7 years of employment as a software developer
M.S, Computer Engineering, M.S, Computer Engineering at Northeastern UniversityBachelor's Degree, Electrical and Electronics Engineering, Bachelor's Degree, Electrical and Electronics Engineering at Shanghai Jiao Tong University
English, Chinese
Github Skills (9)
big-data10
spark10
python10
streaming10
scala10
apidoc9
api9
java7
javas7
Programming languages (3)
Github contributions (5)
apache/spark
Aug 2022 - Apr 2025
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:192 reviews, 41 PRs, 254 comments in 2 years 7 months
Contributions summary:Bo primarily contributed to the Apache Spark project by implementing and improving functionalities related to streaming. They focused on adding Python APIs for Spark Connect, particularly for stateful streaming operations like `dropDuplicatesWithinWatermark`, `mapGroupsWithState`, and `flatMapGroupsWithState`. The user also addressed issues related to error handling and resource management in streaming Python workers, along with adding client-side support for streaming listeners. Their contributions enhance the capabilities of Spark Connect for real-time data processing.
analyticspythondata-processingsqlapache
bogao007/spark
Sep 2022 - Apr 2025
Apache Spark - A unified analytics engine for large-scale data processing
Contributions:247 pushes, 35 branches in 2 years 7 months
analyticsdata-processingapachebig-dataspark
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