Summary
Manuel Martinez is a software engineer with eight years of cross-disciplinary experience building data platforms, ML pipelines, and research infrastructure at institutions including AWS, Fermilab, and the University of Chicago. He blends production-grade cloud engineering—authoring Redshift/S3 lakehouses, Glue/Spark refactors, and CDK-driven CI/CD—with applied research, having migrated research stacks to AWS and delivered scalable mapping and computer-vision pipelines for large scientific and urban projects. Comfortable at the intersection of policy and tech, he’s a CAPP MS candidate who has supported government-facing research and coordinated field deployments for economics studies. Notably, he has driven cost and performance optimizations (e.g., 90% storage reduction and ~80% ETL runtime cuts) and built event-driven replication systems that improved cross-partition data availability. Based in Seattle, Manuel combines rigorous data engineering with domain fluency in urban and scientific research, making him adept at translating analytical needs into auditable, production systems.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Arts (B.A.), Economics, Bachelor of Arts (B.A.), Economics at Southern Connecticut State University
Associate of Arts (A.A.), Liberal Arts and Sciences, General Studies and Humanities, Associate of Arts (A.A.), Liberal Arts and Sciences, General Studies and Humanities at CT State Gateway
Master of Science - MS, Computational Analysis and Public Policy, Master of Science - MS, Computational Analysis and Public Policy at University of Chicago
English, Spanish