Andrew Chen
Chief Technology Officer at Skio
San Ramon, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAndrew Chen is a seasoned technology leader and Chief Technology Officer with 12 years of hands-on experience building scalable cloud-native systems and developer tools from early-stage to growth companies. Based in San Ramon, he leads engineering at Skio, helping major DTC brands adopt subscription commerce, after a multi-year tenure at Databricks where he progressed from intern to tech lead. He blends full-stack engineering, DevOps, and product instincts—contributing to high-profile open-source projects such as MLflow and the Databricks CLI, improving code quality, UX, and cloud automation. An EECS graduate from UC Berkeley, Andrew has a track record of shipping infrastructure and CLI features that enable other engineers and teams to move faster, and his background includes surprising depth in both research labs and production-grade distributed systems.
12 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BS) EECS, Bachelor of Science (BS) EECS at University of California, BerkeleyDougherty Valley High School
Spanish, Chinese
Github Skills (19)
api-rest10
python10
apidoc10
api-design10
restful-api10
command-line-interface10
mlflow10
api10
command-line10
rest-api10
cli10
authentication9
user-authentication9
model-management9
protobuffer9
Programming languages (10)
Github contributions (5)
databricks/databricks-cli
May 2017 - May 2021
(Legacy) Command Line Interface for Databricks
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:20 releases, 37 reviews, 81 commits in 4 years 1 month
Contributions summary:Andrew implemented several features for the Databricks CLI, including support for authentication via tokens, expanding the functionality of the Workspace API, and adding a new Jobs CLI with its associated features. They made changes to core configuration files, added testing frameworks, and updated documentation to reflect the new features. Their contributions added significant value to the CLI, providing enhanced capabilities for users interacting with Databricks services.
command-line-interfacedatabricks
mlflow/mlflow
Jun 2018 - Jul 2019
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Role in this project:Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:50 commits, 106 PRs, 51 pushes in 1 year 1 month
Contributions summary:Andrew primarily contributed to improving the codebase and its documentation. Their work included fixing linter issues related to documentation, adding warnings about running the project on Windows, and including protobuf dependencies. They also made changes to the UI and backend of the platform. Furthermore, the user was involved in enabling PEP8 linting and fixing related errors, improving the overall code quality and maintainability of the repository.
aimlflowmlmodelmachine-learningml
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