Summary
Nathan Maynes is a senior technology leader and data engineer with 11 years of experience designing, building, and managing relational and non-relational data systems for organizations including PBS, Thomson Reuters, and public-sector-focused TrueRoll. He combines hands-on pipeline and knowledge-graph engineering with people leadership—mentoring teams on code quality, architecture, and operational practices while running Technology Services at PBS. Nathan has a track record of integrating disparate systems and streamlining data flows to support decision-making in regulated and mission-driven environments. He holds a master’s in Computer Science from Georgia Tech and has deep practical experience with big data pipelines, graph modeling, and automation. A creative problem solver, he favors leveraging the right tool for the job rather than overengineering, and he’s as likely to prototype in Python as he is to sketch a graph schema. Outside work he’s a podcast enthusiast with a self-deprecating sense of humor about low-level languages, which hints at both curiosity and humility.
11 years of coding experience
6 years of employment as a software developer
B.A., Political Science, B.A., Political Science at Utah State University
High School Diploma, High School/Secondary Diplomas and Certificates, High School Diploma, High School/Secondary Diplomas and Certificates at Fort Zumwalt South
Master's degree, Computer Science, Master's degree, Computer Science at Georgia Institute of Technology
Deep Learning Foundations, Deep Learning, Deep Learning Foundations, Deep Learning at Udacity
German