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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 ensure our services remain fast, reliable, and available as we grow. In this role, you'll own the infrastructure and operational health of Yelp's real-time streaming platform, with Kafka and Flink at its core.
You'll work at the intersection of infrastructure engineering and distributed systems, bringing SRE best practices to an exciting and impactful area of our stack. At Yelp, our systems handle over 300 million business reviews, 100,000 photo uploads, and countless real-time events every day that all move through the dynamic streaming infrastructure you’ll help support and grow.
As a member of our team, you’ll play a key role in maintaining impressive data freshness at scale while having real opportunities for meaningful ownership and innovation. Specifically, you’ll drive automation and self-service so that deploying, upgrading, and scaling streaming infrastructure is as effortless as a git commit and is a code review away.
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.
Own the reliability, scalability, and operational health of Kafka clusters across multi-cloud and hybrid environments
Build and maintain automation for cluster operations, upgrades, capacity scaling, and incident recovery
Partner with engineering teams to enable new streaming use cases, advise on best practices, and ensure data pipeline reliability
Troubleshoot complex issues affecting data flow, performance, or stability, and lead root cause analyses
Execute Kafka version upgrades and platform migrations with minimal disruption to critical services
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!
Solid SRE or infrastructure engineering foundation: experience with infrastructure-as-code (Terraform), configuration management (Puppet, Ansible, or equivalent), cloud platforms (AWS preferred), and Linux operations
Production level experience with Kafka or similar technologies at scale including cluster upgrades, migrations, and capacity planning
Programming proficiency in Python, Java, or similar for tooling and automation
Strong debugging and systems-thinking skills, comfortable tracing data flow issues end-to-end across distributed systems
Nice to Have
There are a variety of factors that go into determining a compensation range, including but not limited to external market benchmark data and years of experience. Based on the anticipated level of experience that we are seeking, we expect the compensation range for this role to be between $141,000 and $216,000 The actual compensation offered may be influenced by a variety of factors, including the candidate’s experience and skill set.
There may be flexibility with the range included in this posting should a candidate be leveled higher or lower than the posted range.
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