Jennifer Grange
Director Of Engineering at Prefect
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolJennifer Grange is a Director of Engineering based in New York with seven years in software development and a steady rise through technical and leadership roles at Prefect, from Software Engineer to Director. She blends hands-on backend Python work—contributing to Prefect's popular workflow orchestration codebase, adding API endpoints, sorting/filtering and test refactors—with product and platform leadership across distributed teams. Her background before tech includes international diplomacy and education roles, giving her uncommon strengths in cross-cultural communication, stakeholder management, and teaching-driven mentorship. Jennifer’s profile reflects a leader who codes, architects, and scales developer-facing systems while translating complex operational needs into reliable platform features.
7 years of coding experience
6 years of employment as a software developer
Master of Science (MSc) International Management (China), Master of Science (MSc) International Management (China) at SOAS University of LondonThe Grace Hopper Program at Fullstack AcademyMaster of Arts (M.A.) Oriental Studies (Chinese), Master of Arts (M.A.) Oriental Studies (Chinese) at University of Cambridge
Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (12)
orchestration10
api10
sqlalchemy10
orchestra10
pytest10
prefect10
python10
apidoc10
data-model10
user-data10
data-set10
data-engineering9
Programming languages (8)
Github contributions (5)
PrefectHQ/prefect
Sep 2019 - Jan 2023
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 releases, 142 reviews, 809 commits in 3 years 4 months
Contributions summary:Jennifer primarily contributed to backend functionality and testing within the Prefect repository. They focused on implementing sorting and filtering capabilities for task runs, flow runs, and deployment data, as well as adding API endpoints. Their work involved modifying various API tests and models, suggesting an understanding of the Orion database architecture. The user also refactored existing code to integrate these features, demonstrating proficiency in Python and related technologies.
pythondataobservabilityml-opsdataflow
bestdan/pifect
Nov 2019 - Feb 2023
Doing stuff with pi
Contributions:11 PRs, 27 pushes, 4 branches in 3 years 3 months
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