Ruifeng Zheng

软件工程师 at Databricks

Changping District, Beijing, China
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts

Summary

🤩
Rockstar
🎓
Top School
Ruifeng Zheng is a software engineer with 11 years of experience, currently building data infrastructure at Databricks in Beijing after senior engineering and technical leadership roles at JD Group and analytics firms. He combines a strong academic foundation from Peking University in information processing theory with hands-on backend and test automation expertise, contributing performance and reliability improvements to the widely used Apache Spark project. Ruifeng has a track record of stabilizing large-scale data processing systems by refactoring complex implementations and expanding test coverage—especially around index and pandas-like APIs—so production behavior is more consistent and maintainable. Comfortable operating at the intersection of engineering, data science, and team leadership, he brings both algorithmic rigor and pragmatic delivery experience to mission-critical analytics platforms.
code11 years of coding experience
book理学硕士, 信息处理理论与技术, 理学硕士, 信息处理理论与技术 at 北京大学
languagesChinese
github-logo-circle

Github Skills (12)

pandas10
apache-spark10
python10
test-automation10
refactor9
data-processing9
refactoring9
data-structure7
data-structures7
algorithm7
algorithms7
datastructures-algorithms7

Programming languages (12)

JavaDockerfileC++ShellScalaJavaScriptGoHTML

Github contributions (5)

github-logo-circle
apache/spark

Sep 2017 - Jan 2023

Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
userBack-end Developer & Test Automation Engineer
Contributions:3317 reviews, 109 commits, 3021 PRs in 5 years 5 months
Contributions summary:Ruifeng primarily contributed to improving the performance and functionality of the Apache Spark data processing engine, with a focus on addressing stability and consistency issues. They were involved in reorganizing and enhancing tests, specifically focusing on index operations, and test coverage for pandas API operations. Their work aimed to ensure the reliability of Apache Spark, and improve code maintainability by refactoring and simplifying implementations.
apache-sparkpythonscalarjava
zhengruifeng/numpy

Jun 2022 - Dec 2025

The fundamental package for scientific computing with Python.
Contributions:10 pushes in 3 years 6 months
pythonndarrayscientific-computing-with-pythonscientific-computingpetsc
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial