Natalie Rud
Senior Data Engineer
Greater Cambridge Area United Kingdom
Summary
👤
Senior🎓
Top SchoolNatalie Rud is a Senior Data Engineer with 10 years of experience building reliable, high-performance data pipelines and cloud-native services across finance, pharma, and SaaS. Skilled in advanced Python, SQL and AWS, she combines hands-on engineering with pragmatic cost and security optimisations—one example being a 75% reduction in DynamoDB export costs via incremental updates. Her background spans QA and test automation for major open-source projects like pandas, where she contributed tests and bug fixes to improve datetime and categorical reliability. At Perkbox and Thoughtworks she has driven data architecture improvements, implemented Delta Live Tables and Unity Catalog governance, and built models for pricing and churn. Trained as an applied mathematician, Natalie brings strong analytical rigour, attention to detail and a knack for uncovering hidden data quality issues that translate directly into business impact.
10 years of coding experience
11 years of employment as a software developer
Master's program listener Theoretical Economics, Master's program listener Theoretical Economics at EERC (Economics Education and Research Consortium) at “Kyiv-Mohyla Academy”Igor Sikorsky Kyiv Polytechnic Institute
English, Ukrainian
Github Skills (8)
pandas10
python10
testing10
data-science9
data-analysis9
pytest7
text-align7
text-alignment7
Programming languages (6)
Github contributions (5)
pandas-dev/pandas
Dec 2016 - Dec 2019
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:5 commits, 5 PRs, 25 comments in 3 years
Contributions summary:Natalie primarily contributed to the testing and quality assurance of the pandas library. Their work involved writing and modifying tests for various functionalities, including `iloc`, `searchsorted`, and `to_datetime` features, and also addressed specific bug fixes related to Categorical data and datetime handling. The contributions included adding new test cases to ensure correct behavior and fixing existing issues that were identified in the library. These changes reflect a focus on improving the reliability and stability of the pandas library.
pythondatalabeled-datamanipulationdataframes
nathalier/timetracker
Jan 2016 - Aug 2016
Contributions:33 commits, 9 pushes, 1 branch in 6 months
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