Coyote Marin
Senior Software Engineer, Front End at Everlaw
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolCoyote Marin is a Senior Front End Software Engineer based in San Francisco with 11 years of experience building production software across startups, biotech, academia, and open source. They combine clean, maintainable front-end work with full-stack experience—having written data pipelines, APIs, and LIMS integrations—and have repeatedly stepped into cross-functional roles that bridge engineers, researchers, and product. An active open-source maintainer, Coyote contributed meaningful Spark/MapReduce runner improvements to the widely used Yelp/mrjob project, easing migrations between Hadoop and Spark. They seek work that does tangible good for the world and bring a history of volunteer leadership on procurement and civic-tech projects that influence policy as well as product.
11 years of coding experience
18 years of employment as a software developer
M.S. Computer Science (Software Engineering Research), M.S. Computer Science (Software Engineering Research) at University of California, BerkeleyCertificate of Achievement Legal/Paralegal Studies, Certificate of Achievement Legal/Paralegal Studies at City College of San Francisco
English, Spanish
Stackoverflow
1reputation
223reached
0answers
2questions
Github Skills (8)
apache-spark10
python10
mapreduce9
hadoop-mapreduce9
data-engineering8
accessibility6
styles6
html6
Programming languages (7)
Github contributions (5)
Yelp/mrjob
Feb 2017 - Nov 2020
Run MapReduce jobs on Hadoop or Amazon Web Services
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 2844 commits, 854 PRs in 3 years 9 months
Contributions summary:Coyote's commits primarily focus on implementing and refining functionality within the mrjob/spark/runner.py file, which is a core component for running MapReduce jobs on Spark. Their work includes adding functionalities like temporary directory setup for Spark runners, removing or adjusting features such as the upload directory, and integrating the handling of various resources that might be used in Spark jobs. These modifications point to the user's work in improving the framework for executing jobs in the Spark environment.
amazonweb-servicessparkamazon-web-servicesmapreduce
spendright/msd
Jul 2015 - Sep 2016
Contributions:24 PRs, 32 pushes, 3 branches in 1 year 2 months
scrapermergedata-scraper
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