Erfan Nariman
Data Engineer
Randstad, Netherlands
Summary
🤩
Rockstar🎓
Top SchoolErfan Nariman is a data engineer and co-founder based in the Randstad with seven years of experience turning complex data into operational value for clients across insurance, retail and financial services. At Zypp he leads data integration, quality and advanced analytics initiatives, building a framework that unifies data management, data science and reporting to drive scalable automation. He has hands-on experience across the full pipeline—from SQL and Python ETL to cloud deployments, CI/CD and visualization—and has taught data analytics and machine learning as a guest lecturer. Erfan has contributed to the widely used pandas library, adding features like ignore_index for explode and improving documentation and tests, underscoring his practical open-source impact. Colleagues describe him as a pragmatic technical lead who pairs client-facing project ownership with deep implementation craft. He combines startup grit with academic teaching experience, enabling clear translation of analytical ideas into production-ready systems.
7 years of coding experience
4 years of employment as a software developer
Vwo/Gymnasium, Vwo/Gymnasium at Walburg College ZwijndrechtDelft University of Technology
Stackoverflow
41,971reputation
15.1mreached
1,237answers
22questions
row
top-5%
pandas
top-1%
sorting
top-5%
regex
top-5%
dataframe
top-1%
docker
top-5%
Github Skills (29)
pytest10
python10
data-science10
testing10
data-manipulation10
pandas10
dataframe10
data-analysis10
row9
datetime9
numpy9
regex9
groupby9
aggregate-functions9
docker9
Programming languages (11)
Github contributions (5)
pandas-dev/pandas
Jun 2020 - Oct 2021
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:
Data Scientist
Data ScientistContributions:53 reviews, 24 commits, 39 PRs in 1 year 4 months
Contributions summary:Erfan contributed to the pandas library by implementing and testing features related to data manipulation and analysis. They added the `ignore_index` option to the `explode` method for both DataFrames and Series, allowing for more flexible index handling. The user also added a test for `groupby` transform on a categorical column and examples for natural sort utilizing the key argument. Furthermore, the user deprecated `DataFrame.lookup` and made various documentation improvements, including fixing code style and adding examples.
pythondatalabeled-datamanipulationdataframes
erfannariman/pandas
Jun 2020 - Dec 2022
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:286 pushes, 58 branches in 2 years 7 months
polarspythondatalabeled-datamanipulation
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