Madison Swain-bowden
Senior Data Engineer
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolMadison Swain-bowden is a Senior Data Engineer with 11 years of experience, currently building data systems at Babylist after a stint as a primary maintainer of Automattic’s Openverse search engine. She specializes in Python, Postgres, and Airflow, and has restored and modernized large-scale pipelines that catalog hundreds of millions of records from heterogeneous web sources. A committed open-source contributor, she has improved core parts of Apache Airflow and contributed significant image-analysis work to CellProfiler, blending backend reliability with scientific computing. Madison pairs hands-on engineering with mentorship and leadership—she’s served as interim team lead and co-chaired community events like PyCascades. Based in Seattle and trained in both Physics and Computer Science, she brings scientific rigor to data engineering problems and a clear focus on building tools that help people and communities. She’s also outspoken about workplace fit and advocacy, having co-led an employee resource group to create safer environments for queer and trans colleagues.
11 years of coding experience
8 years of employment as a software developer
Physics (B.S.) & Computer Science (B.S.) Physics & Computer Science, Physics (B.S.) & Computer Science (B.S.) Physics & Computer Science at Seattle Pacific University
English, Chinese
Github Skills (13)
cellprofiler10
apache-airflow10
python10
image-processing10
documentation10
data-engineering9
scipy9
orchestration9
orchestra9
workflow-engine9
automations8
automation8
pytest8
Programming languages (16)
Github contributions (5)
CellProfiler/CellProfiler
Nov 2017 - Dec 2018
An open-source application for biological image analysis
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:4 releases, 199 commits, 101 PRs in 1 year 1 month
Contributions summary:Madison significantly contributed to the CellProfiler project by implementing and refining various image analysis modules. Their work included the creation of the "RemoveLabeledHoles" module, along with improvements and bug fixes to existing modules like "RemoveHoles" and "FillObjects". They also addressed the integration of new features and performed substantial code refactoring, including converting modules to different object processing types.
image-analysispythonneuroimagingbiologicalmicroscopy
apache/airflow
Jan 2018 - Sep 2024
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:Back-end Developer
Back-end DeveloperContributions:1 review, 13 PRs, 33 comments in 6 years 8 months
Contributions summary:Madison primarily contributed to improving the Apache Airflow codebase by addressing documentation ambiguities, fixing formatting issues, and implementing feature enhancements. Their work involved modifying Python files within the core Airflow library, focusing on areas like task instance handling, logging, and the user interface. Furthermore, the user added notes regarding Variable precedence with env vars and also corrected documentation issues. These changes demonstrate a focus on code quality, usability, and improved documentation.
monitorpythonschedulerapacheprogrammatically
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