William Surles is a Principal Data Engineer with 12 years of experience building distributed data platforms, designing data warehouses, and turning product metrics into actionable business insight. He has led data engineering and data science efforts across SaaS and product teams—deploying reliable pipelines on AWS, Spark, Kubernetes, and Airflow while enabling analytics via Redash, Tableau, and Grafana. Comfortable in both R and Python, he’s solved ML and experimentation problems, instrumented metric collection for feature launches, and presented findings directly to senior leadership. Based in Boulder, he pairs technical depth with a track record of shipping data products for sales and engineering teams, and outside work he tutors middle schoolers in math and science and explores the mountains on his bike—an indicator of his patient teaching style and appetite for complex, long-haul problems.
12 years of coding experience
13 years of employment as a software developer
BS Mechanical Engineering, BS Mechanical Engineering at Clemson University
Data Science Specialization (Johns Hopkins University), Data Science Specialization (Johns Hopkins University) at Coursera
Python and R Career Track Certificates Data Science, Python and R Career Track Certificates Data Science at DataCamp
MS Engineering, MS Engineering at University of Colorado Boulder
Contributions:30 commits, 1 push in 1 year 1 month
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