Nate Kupp
VP Infrastructure at Perplexity
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolNate Kupp is a seasoned infrastructure and data engineering leader with 15 years of experience building scalable data platforms and production systems across Apple, Thumbtack, Dagster Labs, Instacart, and now Perplexity in San Francisco. He combines deep technical roots (Ph.D./M.S. in Electrical Engineering from Yale) with hands-on execution—contributing code and docs to the popular Dagster open‑source orchestration project and implementing tooling for synthetic event generation and parquet data pipelines. At Instacart he led Data Infrastructure efforts to deliver reliable, timely data for the company’s analytics and ML teams, and earlier roles span everything from battery analytics at Apple to low‑level chip characterization at IBM. Nate’s background blends research-caliber rigor with pragmatic platform building, often surfacing improvements in observability and reproducible data workflows that aren’t obvious from org charts alone.
15 years of coding experience
15 years of employment as a software developer
Ph.D Electrical Engineering, Ph.D Electrical Engineering at Yale UniversityB.S Electrical Engineering, B.S Electrical Engineering at The College of New Jersey
Github Skills (11)
dagster10
data-pipelines10
data-pipeline10
python10
data-engineering10
documentation9
scala9
etl9
apache-spark9
analytics8
faker7
Programming languages (6)
Github contributions (5)
dagster-io/dagster
Jan 2019 - Apr 2019
An orchestration platform for the development, production, and observation of data assets.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:3 releases, 23 commits, 76 PRs in 3 months
Contributions summary:Nate made several contributions to the documentation and example code, including updates to the contributing guidelines and refreshing the tutorial to reflect the latest UI. The user implemented an automation tool for generating synthetic event data, utilizing Python and related libraries like Faker. Furthermore, the user added example Scala code to process JSON events and write Parquet files, demonstrating contributions to the project's data processing capabilities.
operationpythonobservationschedulermetadata
trela/qikify
Mar 2011 - May 2012
Contributions:116 commits in 1 year 2 months
data-analysisadaptivelightningsemiconductormachine-learning
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