Top expert inGo Development and Distributed Systems Engineering
Jesse Szwedko is a seasoned software engineer and team lead with 13 years of experience building scalable, production-grade systems across cloud, observability, and payment platforms. Now leading teams at Datadog, he combines hands-on expertise in Go and Python with deep operational knowledge of Cassandra, Kafka, Docker, Terraform and AWS to drive reliability and automation. He has a track record of shipping platform tooling and infrastructure—formerly leading cloud platform efforts at Braintree and contributing to Timber.io before its acquisition by Datadog. An active open-source contributor, Jesse has improved robustness and testing in well-known Go projects (urfave/cli, negroni) and low-level drivers like go-oci8, showing a focus on maintainability and correct data handling. He began his career building integrations and developer tooling at ModCloth and has also driven civic tech and social-good projects, reflecting a practical, mission-oriented approach to engineering.
13 years of coding experience
10 years of employment as a software developer
BS, Computer Science, BS, Computer Science at University of Pittsburgh
Contributions:8 releases, 18 reviews, 122 commits in 6 years 9 months
Contributions summary:Jesse focused on improving the robustness and stability of the `negroni` middleware. They addressed critical issues by implementing early panic checks for nil handlers and ensuring correct content-type handling in the recovery middleware. Further, they enhanced the codebase by documenting middleware usage, refining the response writer's behavior and implementing HTTP/2 pusher support. The user also contributed to better testing and addressing bugs within the system.
Contributions:7611 reviews, 1537 commits, 5125 PRs in 3 years 5 months
Contributions summary:Jesse's contributions primarily focused on enhancing the functionality and maintainability of the Vector data pipeline. They implemented a fix for the regex parser transformation by correctly assigning capture group fields. Moreover, the user updated the CI/CD pipeline by installing Ruby and updating the base images, and also contributed to documentation updates and bug fixes. Further strengthening the CI/CD pipeline, the user also added additional features like automatic tag setting and adding metrics for logging.
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