Nahum Sá is a Senior AI and Data Software Engineer with 7 years of experience building production-grade, cost-optimized data platforms across cloud providers. He translates ambiguous data science goals into scalable architectures using IaC (Terraform), Kubernetes, GCP and AWS, and is fluent in Python, Rust, SQL and Go. Nahum has led Data Mesh and ML platforms that process billions of documents daily, cut latency by 70%, and drove a 60% productivity gain with generative AI features adopted by most users. He combines hands-on engineering—contributing to the rustworkx graph library test suite and implementing new graph generators—with strong stakeholder engagement across domains like supply chain, oil & gas and asset management. With a background in astrophysics and quantum-geophysics research, he brings a rigorous, research-driven approach to solving complex data problems. Based in Brazil, he focuses on end-to-end delivery from data collection and modeling to deployment and observability.
7 years of coding experience
4 years of employment as a software developer
University of Kansas
Física Astrofísica, Física Astrofísica at Universidade Federal de Sergipe
A high performance Python graph library implemented in Rust.
Role in this project:
Backend Developer
Contributions:64 reviews, 9 commits, 8 PRs in 10 months
Contributions summary:Nahum primarily focused on refactoring and enhancing the test suite for the `rustworkx` library, a high-performance Python graph library implemented in Rust. They reorganized test files, particularly for graph and digraph classes, and incorporated new test cases for generators, including those related to the hexagonal and binomial tree graph algorithms. Furthermore, the user implemented the heavy hex and heavy square graph generators. These efforts improved test coverage and expanded the functionality of the graph library.
Contributions:2 PRs, 22 pushes, 2 branches in 3 years 5 months
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