Cathal Coffey is a Staff Engineer with 15 years of experience building scalable, data-driven systems across industry leaders including HubSpot, Intercom, Amazon and Microsoft, and a strong academic background in machine learning and geocomputation. He blends research rigor (PhD work at UC Berkeley and fellowships) with hands-on production engineering, from real-time log enrichment at Amazon to schema-migration contributions on GitHub’s gh-ost. An early open-source author—creator of the widely used DocX library with over 100k downloads—he continues to improve core backend tooling and operational robustness, particularly around MySQL binlog handling and cut-over control. Recognized with multiple academic awards and an Intel medal, he pairs deep systems thinking with pragmatic delivery and mentoring across teams.
14 years of coding experience
11 years of employment as a software developer
Ph.D Candidate CEE Systems Machine Learning, Ph.D Candidate CEE Systems Machine Learning at University of California, Berkeley
Master of Science (MSc) Machine LearningGeocomputation, Master of Science (MSc) Machine LearningGeocomputation at Maynooth University
Contributions:4 reviews, 9 commits, 3 PRs in 7 days
Contributions summary:Cathal contributed to the core logic of the `gh-ost` tool, focusing on the handling of binlog events. Their commits added functionality to process changelog events, specifically related to state and heartbeat updates. They implemented changes to the `migrator.go` file, incorporating new event handling and logging, and also made modifications to context management for heartbeat tracking. These changes improved the tool's ability to monitor and control the schema migration process, specifically around cut-over operations.
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