Edwin Jacox
Senior Software Engineer at MongoDB
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolEdwin Jacox is a Senior Software Engineer based in San Francisco with two decades of professional experience bridging database research and production cloud systems. He holds a Ph.D. in computer science focused on databases and transitioned from bioinformatics postdoctoral work into biotech and large-scale cloud engineering, most recently applying his expertise at Google and now MongoDB. Edwin designs resilient data pipelines and microservices—implementing containerized agents, partition managers, and efficient metrics extraction for high-load systems—and has deep hands-on AWS, Postgres, DynamoDB, S3, and serverless experience. An active contributor to the Toil workflow engine, his work on AWS provisioners and Azure cluster utilities shows a practical grasp of cloud provisioning and fault-tolerant automation. Colleagues rely on him to turn algorithmic rigor into production-ready systems that handle large biological and operational datasets with efficiency and reliability.
9 years of coding experience
21 years of employment as a software developer
Master of Science (M.S.) Computer Science, Master of Science (M.S.) Computer Science at University of MichiganDoctor of Philosophy (Ph.D.) Computer Science (Databases), Doctor of Philosophy (Ph.D.) Computer Science (Databases) at University of Maryland
English, French
Github Skills (11)
aws10
python9
azure8
gcp8
microsoft-azure8
dockers7
docker7
automations7
automation7
terraformer3
terraform3
Programming languages (3)
Github contributions (5)
DataBiosphere/toil
May 2017 - May 2018
A scalable, efficient, cross-platform (Linux/macOS) and easy-to-use workflow engine in pure Python.
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:5 releases, 456 commits, 184 PRs in 11 months
Contributions summary:Edwin's commits primarily focus on the AWS provisioner within the toil repository, demonstrating an understanding of cloud infrastructure and automation. Their contributions include features for configuring and managing Azure clusters, enhancing the functionality of the cluster utilities. Furthermore, the user improved the robustness of the code by addressing potential errors in the provisioning process.
pythoncommon-workflow-languagemesosawsslurm
ejacox/toil
Jun 2017 - Mar 2018
Contributions:46 pushes, 20 branches, 5 tags in 8 months
scalablepythonworkflow-enginecross-platformpure-python
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