Greg Schivley
Senior Software Engineer at Princeton University
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolGreg Schivley is a data-focused energy and environmental software engineer with 11 years of experience turning complex emissions and power-system data into actionable insights for researchers, policymakers, and industry. As Senior Software Engineer at Princeton’s ZERO Lab and owner of Carbon Impact Consulting, he designs end-to-end Python data pipelines, machine learning models, and visualizations that surface the climate impacts of energy technologies and policies. He contributes to the widely used PUDL open-data project, building ETL processes that integrate EPA IPM spreadsheets into an analysis-ready utility database. His background blends a PhD in Environmental Engineering with practical consulting for DOE and private clients, and he’s equally comfortable prototyping research tools and production-grade data systems. Based in Camden, Maine, he also brings entrepreneurial experience as co-owner of a hospitality business, reflecting a pragmatic, hands-on approach to problem solving.
11 years of coding experience
8 years of employment as a software developer
BS, Physics, BS, Physics at Allegheny CollegeDoctor of Philosophy (Ph.D.), Environmental Engineering, Doctor of Philosophy (Ph.D.), Environmental Engineering at Carnegie Mellon University
Github Skills (8)
etl10
pandas10
data-pipeline10
python10
data-engineering10
sqlalchemy9
open-data9
sqlite7
Programming languages (7)
Github contributions (5)
catalyst-cooperative/pudl
Jun 2018 - Jun 2019
The Public Utility Data Liberation Project provides analysis-ready energy system data to climate advocates, researchers, policymakers, and journalists.
Role in this project:
Data Engineer
Data EngineerContributions:37 commits, 3 PRs, 79 comments in 1 year
Contributions summary:Greg primarily contributes to the ETL processes within the PUDL project. Their work focuses on extracting, transforming, and loading data from EPA's Integrated Planning Model (IPM). They implemented data extraction from different spreadsheet formats, developed data transformation functions, and integrated the IPM data into the PUDL database schema, demonstrating a strong focus on data pipeline development. The user also made changes to the datastore and constants modules to handle different data sources and file structures.
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gschivley/CCS-climate
Feb 2017 - Oct 2019
Contributions:2 PRs, 21 pushes, 4 branches in 2 years 8 months
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