Charles Cash is a Machine Learning Solution Architect with 12 years of experience designing and shipping end-to-end data producers, consumers, and processors for enterprise-scale systems. He blends hands-on engineering—Python, Airflow, Kubernetes, Terraform, Golang—and pragmatic architecture to migrate, productionize, and improve data platforms across companies like phData, Astronomer, StockX, and Nike. Charles has repeatedly turned Airflow and ETL proofs-of-concept into robust production workflows, introduced data quality with GreatExpectations, and automated infra with Terraform to drive measurable business outcomes. He contributes to open source (including Apache Airflow and practical UI/PGP work on the Felony project) and often pairs platform-building with developer enablement and documentation. Based in Clarksville, Michigan, he’s known for surfacing small but impactful improvements—like logging, verification UX, and tooling for credential and lineage management—that reduce operational friction at scale.
12 years of coding experience
9 years of employment as a software developer
Associate's degree Computer Science, Associate's degree Computer Science at Valencia College
Contributions:31 commits, 6 PRs, 24 pushes in 13 days
Contributions summary:Charles primarily focused on enhancing the user interface and functionality of the Felony application, which is a PGP messaging application. They addressed UI issues like title bar styling, implemented features such as a "nevermind" option during encryption/decryption, and added functionality to notify users if verification fails due to a missing contact. The developer also added logging to alias and keychain actions. The commits indicate a good understanding of React, Electron, and PGP integration.
Contributions:3 releases, 20 commits, 14 pushes in 1 year 5 months
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