Top expert inData Engineering and Analytics Technologies
Maxime Beauchemin is the founder of Preset and the creator of Apache Airflow and Apache Superset, bringing 14 years of experience building data infrastructure and visualization tools from California. He combines entrepreneurial leadership with hands-on full‑stack engineering across data orchestration, analytics, and connector development. An active open-source maintainer, his work spans front-end charting and UI packages for Superset, back-end SQL/time-grain handling, and extending Druid connectors with features like limit specs, regex filters and pandas export. Comfortable toggling between high-level architecture and nitty-gritty details, he has improved APIs and UX alike—everything from CRUD and error handling in Flask-AppBuilder to map coverage and chart scrolling tweaks. Maxime’s track record is shipping product-quality open-source systems that make complex data workflows accessible to analysts and engineers.
Contributions:9 reviews, 62 commits, 107 PRs in 7 years 4 months
Contributions summary:Maxime primarily contributed to enhancing the `pydruid` library, a Python connector for Druid. Their work included adding support for features like limit specifications and regex filters within the query functionality. The user also addressed compatibility issues, specifically fixing string type checks in Python 2, and implemented functionalities such as pandas export for select queries. They also improved code quality by linting with flake8 and adding scan query support.
Apache Superset is a Data Visualization and Data Exploration Platform
Role in this project:
Full-stack Developer
Contributions:9 releases, 1386 reviews, 2369 commits in 7 years 6 months
Contributions summary:Maxime contributed to both the front-end and back-end aspects of the Apache Superset project. Their commits primarily involved front-end development, with the implementation of features such as chart customizations and the improvement of the table editor. They also made back-end modifications, particularly around the visualization flow for data access, and they contributed to database interaction by enhancing the handling of time grains and SQL query processing.
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