Teddy Crepineau is a founding software engineer with a decade of experience building AI-native data platforms, observability, and ML-powered automation. He specializes in scalable backend systems and data ingestion, having shipped anomaly detection, incident inference, multithreaded profiling, and observability APIs at Collate while contributing backend improvements to the prominent open-metadata project. Comfortable across Python, Java, Go, Postgres, Elasticsearch and AWS, he combines hands-on implementation with CI/CD and testing discipline to deliver reliable, memory-conscious solutions. Teddy’s background spans data platform architecture, ELT frameworks and product-facing analytics, and he’s notable for turning complex profiling and lineage challenges into pragmatic, production-ready features. Based in Paris, he blends technical depth with cross-functional leadership—writing technical specs, coordinating frontend/design teams, and improving test coverage to accelerate product delivery.
10 years of coding experience
6 years of employment as a software developer
Master's degree Strategic Management & Marketing Innovation, Master's degree Strategic Management & Marketing Innovation at University of the Pacific
Associate's Degree Marketing, Associate's Degree Marketing at University of Montpellier
Bachelor's Degree General Management, Bachelor's Degree General Management at Toulouse School of Management
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration.
Role in this project:
Back-end Developer
Contributions:2 releases, 1132 reviews, 166 commits in 1 year 2 months
Contributions summary:Teddy primarily focused on back-end development tasks, including refactoring code, integrating and utilizing helper functions. A significant portion of the work involved modifying and integrating code from utils.helper to multiple source files. The commits demonstrate a focus on improving the codebase, and adding support for different features and configurations of the platform.
Twitter sentiment is a Python library leveraging NLP and the Twitter API to determine the emotion of a tweet
Contributions:107 commits, 10 PRs, 89 pushes in 4 months
nlpapipython-librarypythonemotion
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Teddy Crepineau - Founding Software Engineer at Collate