Jason M is an experienced software and data engineer with 11 years building maintainable, enterprise-grade systems across cloud infrastructure, distributed computing, and cybersecurity. He blends model-based systems thinking with strong quantitative instincts—grounded in a B.Sc. in Biology and a Mathematics minor from UC San Diego—to deliver practical ML/AI-driven solutions. Jason has hands-on experience optimizing BigQuery pipelines and query performance, including contributions to GoogleCloudPlatform's professional-services repo and extensions like the BigQuery z/OS Mainframe Connector. Based in New York, he thrives at the intersection of data engineering and cloud-native tooling, turning complex data workflows into auditable, production-ready services.
Common solutions and tools developed by Google Cloud's Professional Services team. This repository and its contents are not an officially supported Google product.
Role in this project:
Data Engineer
Contributions:21 reviews, 26 commits, 27 PRs in 3 years 11 months
Contributions summary:Jason primarily contributed to the development of tools and solutions related to BigQuery within the Google Cloud Platform. Their work includes creating a BigQuery query plan exporter and a BigQuery pipeline tool, which likely involve data extraction, transformation, and loading (ETL) processes. These tools suggest a focus on optimizing query performance and managing data workflows within the BigQuery environment. Additionally, the user added support for the BigQuery z/OS Mainframe Connector, and added new features, which further extends the functionality for data integration.
Contributions:2 pushes, 1 branch in 2 years 7 months
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