Summary
Paul Anzel is a Staff Data Engineer with 11 years of experience building performant data platforms, ETLs, and production ML workflows, currently leading data efforts at Rev. He has a proven track record of cutting compute and query times dramatically, architecting data marts with dbt, and consolidating tooling to lower costs and complexity at scale. Comfortable across the full data lifecycle, Paul has moved models from research to production, implemented robust alerting and data-quality systems, and standardized Python/Databricks development practices. His background spans startups to enterprise retail and SRE-adjacent work—bringing statistical physics rigor from a Caltech MS to practical solutions in transportation- and energy-adjacent domains. Outside of work he pursues public-transit exploration and plays the accordion, a hint at his curiosity for systems both technical and cultural.
11 years of coding experience
8 years of employment as a software developer
Bachelor of Science (BS) Chemical Physics, Bachelor of Science (BS) Chemical Physics at Rice University
California Institute of Technology