George Wu is a software engineer with a decade of experience building reliable backend and cloud-native systems, currently at Datadog after senior engineering roles at Imply and AWS. He specializes in backend and DevOps work, with practical experience improving Kubernetes task runners for Apache Druid—contributions that increased observability and stability in a high-performance analytics database. Comfortable across production services and container orchestration, he has a track record of shipping bug fixes, new features, and unit-tested improvements that reduce operational surprises. A UC Berkeley-trained mathematician and computer scientist, he brings rigorous problem-solving to distributed systems challenges. Based in New York, he pairs large-company engineering discipline with open-source collaboration, often focusing on edge cases that improve long-term reliability. Colleagues rely on him for practical, test-driven fixes that make complex infrastructure more observable and robust.
10 years of coding experience
7 years of employment as a software developer
BA Mathematics and Computer Science, BA Mathematics and Computer Science at University of California, Berkeley
Apache Druid: a high performance real-time analytics database.
Role in this project:
Backend & DevOps Engineer
Contributions:235 reviews, 122 PRs, 56 pushes in 2 years 5 months
Contributions summary:George primarily worked on the Kubernetes task runner extension for Apache Druid. Their contributions focused on addressing bugs, implementing new features, and improving stability. They addressed issues related to handling deleted Kubernetes jobs and null pointer exceptions, thereby improving reliability. They also added new error messages, unit tests, and added labels to the k8s jobs to increase observability.
Apache Druid: a high performance real-time analytics database.
Contributions:373 pushes, 71 branches in 1 year 10 months
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