Staff Software Engineer, Metrics Team

Uber is seeking a Staff Software Engineer to join their M3 Metrics team, a crucial component of their observability data platform. This role involves working on a cutting-edge distributed metrics solution that processes over 4 billion metrics per second and handles 20K queries per second. The position offers an exciting opportunity to tackle complex distributed system challenges at massive scale.

The M3 Metrics team is responsible for delivering a comprehensive end-to-end distributed metrics solution that operates at Uber's impressive scale. As a Staff Software Engineer, you'll be working on solving fundamental challenges in large-scale distributed systems, including scalability, availability, performance, and efficiency. The role also focuses on providing intelligent insights to identify potential issues before they impact customers, ensuring a seamless experience for millions of users worldwide.

The position requires a strong background in backend development with at least 8 years of experience in languages like Java or Go. You'll need to demonstrate expertise in designing and implementing large-scale distributed backend services, along with a proven track record of building and operating highly reliable systems at scale. Experience with OpenTelemetry and monitoring infrastructure tools like Prometheus, Kibana, and Grafana is highly valued.

This is an excellent opportunity for a senior-level engineer looking to make a significant impact at a global technology leader. You'll be working with a dynamic, diverse team that values technical excellence and innovation. The role offers competitive compensation, including a base salary range of $218,000-$242,000, along with bonus potential, equity awards, and comprehensive benefits. The position follows a hybrid work model, requiring at least 50% of work time in the office to maintain collaboration and cultural identity.

Join Uber's M3 Metrics team to help shape the future of observability at scale and tackle some of the most challenging problems in distributed systems. Your work will directly impact the reliability and performance of Uber's global platform, making a difference in the lives of millions of users worldwide.