Haejoon Lee
Committer, Apache Spark at The Apache Software Foundation
Seoul, South Korea
Summary
🤩
RockstarHaejoon Lee is a committed backend engineer and Apache Spark committer with 7 years of experience building and hardening large-scale data processing systems. Based in Seoul, he has driven pandas API on Spark improvements and protobuf/LaTeX integrations within Apache Spark while previously contributing test automation and QA refinements to the popular Delta Lake project. His background spans production roles at Databricks and Mobigen, giving him hands-on experience from feature development to rigorous test coverage in distributed analytics stacks. Known for cleaning up deprecated APIs and improving parity with pandas, he blends careful maintenance with feature delivery to keep ecosystem tools reliable and consistent. An underappreciated strength is his dual focus on developer-facing APIs and low-level test suites, which helps prevent regressions as Spark and Lakehouse tooling evolve.
7 years of coding experience
8 years of employment as a software developer
Github Skills (20)
spark-sql10
delta-lake10
python10
testing10
dataframes10
pandas10
time-series10
dataframe10
api-design9
data-structure9
algorithm9
algorithms9
scala9
apidoc9
api9
Programming languages (6)
Github contributions (5)
apache/spark
Sep 2020 - Jan 2023
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:1648 reviews, 56 commits, 595 PRs in 2 years 4 months
Contributions summary:Haejoon primarily focused on enhancing the pandas API on Spark, contributing to its core functionalities. They cleaned up deprecated APIs and introduced proper warning messages for deprecated functions, contributing to the project's maintenance. Furthermore, they developed new features such as support for `from_protobuf` and `to_protobuf` for SQL functions and improvements in the `DataFrame.to_latex` and `Series.to_latex`. They also contributed to the implementation of the `getCondition`, and other pandas API functionalities, ensuring that pandas API on Spark is consistent with Pandas.
analyticspythondata-processingsqlapache
delta-io/delta
Dec 2022 - Dec 2022
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:1 commit in 1 day
Contributions summary:Haejoon's contributions primarily revolve around testing within the delta-io/delta repository. They modified existing test suites, including DeltaDDLUsingPathSuite, DeltaAlterTableTests, MergeIntoSuiteBase, UpdateSuiteBase, DeleteSuiteBase and DeltaTableCreationTests. Their work involved refactoring test code, updating assertions, and modifying the tests to cover different edge cases and error scenarios. The commits also involved updating tests related to Iceberg integration.
analyticsprestodbflinkbig-dataspark
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