Owen Christie
Backend Engineer, Data
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolOwen Christie is a backend and data engineer with nine years of experience building and maintaining production data pipelines across media and commerce domains. Currently at Stripe, he previously shaped subscription and revenue reporting at The New York Times, aligning cross-team data definitions and shipping anomaly-detection tooling used for public reporting. He has strong hands-on expertise in BigQuery/DBT, Spark/Scala, PySpark, Airflow, Go, Terraform and cloud platforms (GCP/AWS), and has led on-call ownership of critical pipelines that serve marketing, finance and support systems. Earlier roles at ENJINE and Outland show he optimizes long-running jobs and data lakes—cutting runtimes from days to hours—and delivers end-to-end systems from mobile apps to ML-ready pipelines. Comfortable bridging product and platform needs, he combines pragmatic engineering with operational discipline and a curiosity for tooling that prevents problems before they surface. Outside work he maintains a personal site and has contributed to open-source tooling for portfolio optimization, reflecting a broad interest in applied data engineering.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Western University
Github Skills (36)
expressjs10
gofmt10
python10
data-science10
data-manipulation10
dataframes10
autopep810
pandas10
formatter10
manipulation10
pre-commit-hook10
data-structures10
yapf10
frame10
data-analysis10
Programming languages (4)
Github contributions (5)
enjine-com/mcos
Jan 2020 - Feb 2020
Implementation of Monte Carlo Optimization Selection from the paper "A Robust Estimator of the Efficient Frontier"
Contributions:73 commits, 3 PRs, 68 pushes in 25 days
optimizationmultiobjective-optimizationmonte-carloselectionefficient-frontier
kastkeepitjumpinlikekangaroos/pandas
Oct 2024 - Feb 2025
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Contributions:33 pushes, 1 branch in 3 months
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