Donne Martin
Software Engineer, Privacy Infrastructure at Meta
Washington, District of Columbia, United States
Summary
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Top expert inPython Ecosystem Development and Data Science
Donne Martin is a software engineer and privacy infrastructure tech lead at Meta with 12 years of experience building systems that protect over three billion people. He blends hands-on engineering, people leadership, and product-minded infrastructure work—from leading integrity teams to architecting privacy review platforms. An avid open-source maintainer, Donne created and contributed to widely used developer tools and learning resources (most notably the System Design Primer with 200k+ stars) and multiple CLIs and data-science notebooks. His background spans cloud and data engineering at Vectorworks (Kinesis, Redshift, Spark) and deep practical expertise in Python tooling, DevOps automation, and scalable backend design. Based in Washington, D.C., he pairs rigorous CS training (BS/MS) with a track record of shipping robust, auditable systems. He brings a pragmatic focus on observability, automation, and developer ergonomics that surfaces across both enterprise and open-source projects.
12 years of coding experience
16 years of employment as a software developer
Johns Hopkins UniversityBS, Computer Science, BS, Computer Science at University of Virginia
English, Tagalog
Stackoverflow
1reputation
0reached
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0questions
Github Skills (72)
dependency-management10
cloud-computing10
python10
testing10
command-line-interface10
bash10
packing10
design-patterns10
linked-list10
code-cleanup10
scikit10
pandas10
numpy10
github-api10
binary-search-tree10
Programming languages (13)
Github contributions (5)
donnemartin/data-science-ipython-notebooks
Jan 2015 - Jan 2018
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Role in this project:
Data Scientist
Data ScientistContributions:528 commits, 51 PRs, 497 pushes in 3 years
Contributions summary:Donne primarily contributed to the development of reusable snippets for data wrangling and machine learning tasks. They created utility classes for common data transformation tasks and statistical analysis, including the definition of a function to calculate the mean height, and implemented algorithms for a nearest neighbor classifier applied to the MNIST dataset. The user's code demonstrates an understanding of machine learning concepts, as well as the practical application of techniques like data manipulation and the use of established data science libraries.
awsbig-datacaffecommand-linedata-science
donnemartin/dev-setup
Jul 2015 - May 2017
macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.
Role in this project:DevOps Engineer
DevOps EngineerContributions:329 commits, 48 PRs, 265 pushes in 1 year 10 months
Contributions summary:Donne focused on setting up a comprehensive macOS development environment, automating tool installations, and streamlining various development workflows. Contributions included creating and modifying shell scripts (`brew.sh`, `aws.sh`, `pydata.sh`, `osx.sh`, etc.) to install software, configure the system, and manage dependencies. They also integrated AWS CLI autocompletion and managed virtual environments for different Python projects, demonstrating expertise in automation and environment management.
android-developmentawsbashhadoop-mapreduceheroku
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