Chloe Kim is a program manager with 8 years of experience blending technical back-end engineering contributions and cross-functional project leadership in the biopharma sector. Based in Singapore, she recently moved into a Program Manager 2 role at Lonza after four years managing complex projects at Samsung Biologics, bringing domain knowledge in biologics process and regulated product delivery. Technically hands-on, Chloe has contributed to open-source back-end projects such as Dozer (real-time CDC data movement) and FINOS Legend Engine, implementing SQL features, aggregation type support, and persistence/bitemporal logic—signals of a strong systems mindset beyond typical PM duties. She pairs rigorous technical problem-solving with stakeholder coordination, able to translate low-level data model decisions into auditable, production-ready workflows. Her background in biological science underpins a rare combination of life-sciences domain fluency and practical software engineering experience.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Biological Science/Bioengineering, Bachelor of Science - BS, Biological Science/Bioengineering at 인하대학교
Dozer is a real-time data movement tool that leverages CDC from various sources and moves data into various sinks.
Role in this project:
Back-end Developer
Contributions:253 reviews, 81 commits, 151 PRs in 4 months
Contributions summary:Chloe contributed significantly to the `dozer` project, focusing on back-end functionality. Their commits centered on implementing new scalar functions like `UCASE()` and refactoring existing aggregator functions such as `SUM` and `COUNT`. They also added support for data types in aggregation, like `Decimal`, `UInt`, `Timestamp`, and `Date`, and enhanced SQL features by adding support for select wildcard.
Contributions:8 reviews, 5 commits, 13 PRs in 2 months
Contributions summary:Chloe contributed to the Legend Engine module, focusing on persistence and relational database interactions. Their work involved adding modules, defining data models, and implementing persistence test scenarios. The commits demonstrate the user's involvement in building the persistence layer, including the integration of new functionalities like delete indicators and bitemporal delta logic. The user also addressed code review comments, which included refactoring and fixing typos.
modelinglegend
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