Miles Granger is a Technical Lead and consultant with over a decade of hands-on experience building cloud-native data platforms, ML pipelines, and open-source data tooling. He combines an MSc in Data Science, a background in the US Air Force, and deep AWS/cloud architecture expertise to deliver serverless-first, production-grade solutions using Python, Rust, and C++. An active contributor to Apache Arrow and Dask, Miles has extended Parquet support and improved critical data kernels—work that underpins high-performance analytics used across the data ecosystem. He runs popular open-source projects such as cramjam (a zero-dependency compression library with millions of monthly downloads) and gilknocker, reflecting a focus on practical performance diagnostics. Known for test-driven development, clear communication, and pragmatic engineering, he helps organizations turn strategic ideas into reliable, maintainable systems.
10 years of coding experience
8 years of employment as a software developer
Master of Science (MSc), Data Science, Master of Science (MSc), Data Science at Lewis University
Associate of Science (A.S.), Logistics, Materials, and Supply Chain Management, Associate of Science (A.S.), Logistics, Materials, and Supply Chain Management at Community College of the Air Force
Bachelor of Science (B.S.) Business Administration, Accounting, Bachelor of Science (B.S.) Business Administration, Accounting at The University of Montana
Contributions:77 reviews, 29 PRs, 62 comments in 8 years 1 month
Contributions summary:Miles contributed to the Dask library by adding and updating documentation for the "Data Transfer" section within the dashboard. They also implemented support for `DataFrame.set_index(..., sort=False)`, enhancing the DataFrame indexing functionality. Further contributions included refactoring tests related to quantile calculations and adding the initial implementation of the Resampler and Rolling APIs, indicating involvement in data manipulation and time series functionalities within the library. Several commits also included fixes to improve the library's stability and performance.
Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics
Role in this project:
Back-end Developer
Contributions:179 reviews, 35 commits, 38 PRs in 4 months
Contributions summary:Miles primarily contributed to the Python and C++ code within the Apache Arrow project, focusing on extending the Parquet integration. Their work includes implementing new features such as `get_stream` for random access files, improving the `list_slice` kernel, and supporting expression filters. They also addressed bug fixes related to nested structures and ensured proper file closing within the ParquetFile and ParquetDataset classes.
apache-arrowarrowparquet
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