Jee Rim
Software Engineer at Datadog
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolJee Rim is a software engineer with nine years of experience based in New York, currently building backend systems at Datadog since 2016. With a PhD in Materials Science from Stanford and prior data science work at Capital One Labs, Jee brings a research-driven, analytical approach to production software. At Datadog they made notable open-source contributions to the widely used datadog-agent, implementing a probabilistic GKArray quantile sketch and integrating distribution metrics into DogStatsd for more efficient percentile telemetry. Their work sits at the intersection of high-performance systems and observability, improving how large-scale metrics are aggregated and transmitted. Comfortable moving between deep algorithmic problems and pragmatic engineering trade-offs, Jee leverages academic rigor to solve real-world infrastructure challenges. Colleagues value their ability to translate complex statistical techniques into robust, production-ready features.
9 years of coding experience
2 years of employment as a software developer
Master's degree, Materials Science, Master's degree, Materials Science at Pohang University of Science and TechnologyDoctor of Philosophy (PhD), Materials Science, Doctor of Philosophy (PhD), Materials Science at Stanford University
Korean
Github Skills (4)
metric10
go10
go-testing9
distributed-tracing5
Programming languages (4)
Github contributions (5)
DataDog/datadog-agent
Jun 2017 - Jan 2018
Main repository for Datadog Agent
Role in this project:
Back-end Developer
Back-end DeveloperContributions:51 commits, 9 PRs, 15 pushes in 7 months
Contributions summary:Jee contributed significantly to the Datadog Agent's percentile sketch functionality, adding a distribution metric type to the DogStatsd parser and aggregator components. They implemented the GKArray, a probabilistic quantile sketch algorithm, enabling the generation of percentile sketches. The user also integrated the sketch series with the v2 endpoint for efficient data transmission, thus improving the monitoring capabilities.
golangdatadog-agentagentobservabilitypmm
jeerim/documentation
Dec 2016 - Jan 2017
Contributions:8 pushes, 1 branch in 14 days
datadogdocumentation-site
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