Calder Myers is a data engineer with a decade of experience building reliable, production-grade data pipelines and turning messy analytics into usable warehouse assets. Based in Oakland, he has progressed from curriculum and analytics roles into engineering leadership, shipping end-to-end solutions with Python, Airflow, Postgres/Presto, AWS services, and pragmatic data modeling. At Pathstream he was the first full-time data engineer who bridged product, analytics, and engineering to replace brittle integrations with well-shaped marts, and he later scaled that expertise at Afresh before joining Meta. He combines a background in technical curriculum design and creative writing with hands-on engineering, which helps him communicate complex data systems clearly to cross-functional teams. Colleagues rely on him to reduce tedium and boost efficiency—automating repetitive workflows so teams can focus on insight.
10 years of coding experience
6 years of employment as a software developer
MA MFA English Creative Writing, MA MFA English Creative Writing at San Francisco State University
Data Science Immersive Data Science, Data Science Immersive Data Science at Galvanize Inc
BA English/Creative Writing // focus areas in Visual Art and Mathematics, BA English/Creative Writing // focus areas in Visual Art and Mathematics at Randolph College
various methods toward creating an ensemble garment extraction model
Contributions:51 commits, 16 PRs, 85 pushes in 1 year 8 months
nlpextractionpythonensemblemodel-extraction
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