Senior Software Engineer - REDAPL Compute at Datadog
North Kingstown, Rhode Island, United States
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Summary
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Jo-ann Meunier is a senior backend engineer with about a decade of experience building large-scale distributed systems, currently focused on REDAPL Compute at Datadog. She designs and operates Go-based backend platforms that read and write to distributed storage used across dozens of high-profile products, leveraging Postgres, Elasticsearch, Kafka and Kubernetes. Previously she led backend work on Datadog’s Database Monitoring product, shipping features like load sampling, SQL Server and Oracle support, and an APM‑DBM link. Her background includes high-throughput Java systems at New Relic handling tens of millions of requests per minute and early firmware and test engineering roles that give her strong systems and hardware-adjacent debugging skills. An active contributor to Datadog’s open-source integrations-core, she added database monitoring functions and live-query support for Postgres, improving real-world observability tooling. Based in Rhode Island, she combines pragmatic cross-team collaboration with a track record of quickly delivering robust, production-grade features.
10 years of coding experience
8 years of employment as a software developer
Bachelor of Science (B.S.) Electrical Engineering, Bachelor of Science (B.S.) Electrical Engineering at University of Rhode Island
Master of Science (M.S.) Computer and Software Engineering, Master of Science (M.S.) Computer and Software Engineering at Boston University
Contributions:550 reviews, 132 commits, 213 PRs in 1 year 4 months
Contributions summary:Jo-ann contributed to the Datadog Agent integrations core, implementing features for database monitoring. They added new functions, such as `database_monitoring_query_activity`, to report database activity events. Additionally, the user added support for live queries in the Postgres integration and made improvements to the SQL Server integration by adding active sessions monitoring and cloud metadata support. Furthermore, the user fixed bugs and improved the efficiency of the SQL Server query metrics collection.
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