Hyunwoo Park
Software Engineer at Amazon
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolHyunwoo Park is a software and data engineer with 9 years of experience building large-scale data platforms and API services, currently developing advertising analytics APIs at Amazon Ads. He has a proven track record of designing end-to-end batch and streaming pipelines, cutting cloud costs and system load through architecture changes (e.g., 30% AWS cost reduction and significant shuffle/load reductions). At Kakao and Mobigen he scaled systems to handle petabyte data, high-throughput clusters, and optimized Spark for locality and performance. An active open-source contributor, he improved pandas-on-Spark (Koalas) behavior and multi-index support, aligning it closer to pandas. With an MS in Electrical and Electronic Engineering from Yonsei and hands-on experience across startups and large platforms, he blends algorithmic rigor with production-grade engineering. He’s particularly skilled at turning messy, fragmented logs and legacy systems into reliable, observable data products that enable AI/ML use cases.
9 years of coding experience
7 years of employment as a software developer
Master M.S. in Electrical and Electronic Engineering, Master M.S. in Electrical and Electronic Engineering at Yonsei University
English, Korean
Stackoverflow
31reputation
7kreached
1answer
2questions
Github Skills (14)
dataframes10
pandas10
time-series10
unit-test10
python10
dataframe10
data-science9
spark9
big-data9
pip6
centos6
apache-spark6
cmake6
mitk6
Programming languages (5)
Github contributions (5)
databricks/koalas
Dec 2019 - Jun 2020
Koalas: pandas API on Apache Spark
Role in this project:
Data Scientist
Data ScientistContributions:15 commits, 22 PRs, 78 comments in 5 months
Contributions summary:Hyunwoo contributed to the Koalas project by addressing issues related to data representation and functionality, aligning Koalas' behavior more closely with Pandas. This involved fixing output formats of the `Series` class to match Pandas, and implementing multi-index support for the `DataFrame.filter` and `Series.filter` methods. Furthermore, the user added and improved tests, especially for the `Series` class, enhancing the library's reliability and providing examples of correct usage.
polarspythonpydatadataframesdata-science
beobest2/nugu_project
Nov 2018 - Nov 2018
Contributions:78 commits, 1 PR, 67 pushes in 5 days
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.