About the role
ABOUT SENTRY
Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building.
Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future.
ABOUT THE ROLE
Sentry helps over 4 million developers understand and resolve issues in their applications. Behind every error, performance trace, replay, and log is a large-scale data platform responsible for storing, querying, and analyzing massive volumes of telemetry data.
We're looking for an Engineering Manager to lead our Events Analytics Platform (EAP) team, which builds and operates the distributed data systems powering Sentry's products. The team manages petabytes of data and develops high-performance analytical infrastructure using technologies like ClickHouse, enabling fast, complex queries across billions of records.
As Sentry grows, so do the technical challenges. The team is evolving its storage and query infrastructure to support increasing data volumes, more complex analytical workloads, and unified access to different types of telemetry data. EAP also provides the data foundation for Seer, Sentry's AI-powered debugging agent, enabling AI systems to access the production context needed to investigate and resolve issues.
In this role, you'll lead a team of engineers tackling complex distributed systems challenges while balancing architectural improvements with the reliability and performance of production systems. You'll bring strong technical judgment, guide engineering decisions, and work closely with product engineering teams to build capabilities that directly impact the developer experience.
This is an opportunity to lead a critical part of Sentry's infrastructure, solve challenging problems at scale, and shape how developers and AI-powered tools interact with application data.
WHAT YOU'LL DO
- Lead and develop a team of engineers working on large-scale distributed data systems, fostering technical excellence, ownership, collaboration, and professional growth.
- Drive technical execution and architectural decisions across EAP's storage and query infrastructure, balancing scalability, reliability, performance, and long-term maintainability.
- Build and evolve analytical data systems supporting complex queries, high-throughput workloads, and efficient access to petabytes of event data.
- Guide the evolution of EAP's architecture, including query optimization, storage and compute separation, and the unification of different event types into a common analytical platform.