Site Reliability Engineer, Core Streaming Remote - United States

Summary

Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we’re all about helping our users, growing as engineers, and having fun in a collaborative environment.

Do you want to help build and operate scalable, resilient systems that power Yelp’s critical business functions? Our Site Reliability Engineers (SREs) ensure our services remain fast, reliable, and available, even as we grow and requirements evolve. As an SRE specializing in Kafka, you’ll play a pivotal role in managing our real-time data streaming infrastructure and supporting event-driven applications at scale.

We work at the intersection of software development and distributed systems, owning the backbone of our organization’s streaming architecture. As a Kafka SRE, you’ll take on challenges only found at the kind of scale that supports global, always-on applications. Yelp processes massive amounts of user data daily—over 300 million business reviews, 100,000 photo uploads, and countless check-ins. Maintaining sub-minute data freshness with such high volume presents an exciting technical problem and a very interesting area to work in.

You'll drive best practices in automation and self-service, knowing that deploying or upgrading data streaming infrastructure should be as effortless as a git commit and code review away.

This opportunity is fully remote and does not require you to be located in any particular state within the US. We welcome applicants from throughout the US. We’d love to have you apply, even if you don’t feel you meet every single requirement in this posting. At Yelp, we’re looking for great people, not just those who simply check off all the boxes.

What you'll do:

Design, deploy, and maintain large-scale Kafka event streaming infrastructure across hybrid and multi-cloud environments.

Collaborate with engineers to enable new features, ensure data pipeline reliability, and advise on best practices for real-time data processing.

Execute and automate Kafka cluster upgrades, migrations, and major version rollouts with minimal impact to critical services.

Build or enhance self-service capabilities and automation for cluster operations, scaling, and incident recovery.

Troubleshoot complex issues affecting data flow, performance, or stability, and drive root cause analyses.

Participate in on-call rotations. Our geographically distributed SRE teams use a “follow-the-sun” model, so no one needs to be on-call 24 hours a day!

What it takes to succeed:

Strong hands-on experience designing and implementing large-scale Kafka event streaming capabilities in production, across