About the role
We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us!
Your Opportunity
New Relic gives engineering teams real-time insight into their software and infrastructure, so they can find and fix problems fast. The Pipeline Control team builds and runs the product that manages customers’ telemetry pipelines: ingesting, routing, transforming and delivering telemetry at GB/s scale. If those pipelines are slow or down, our customers notice.
As a Senior Software Engineer on the team, you will own services in production end to end: you’ll build them, deploy them, monitor them and support them. You’ll work with Go, Java, Kafka, Kubernetes and AWS, and grow your skills in large-scale observability systems.
What You’ll Do
- Build and operate big-data-scale pipeline services that ingest, route, transform and deliver telemetry at GB/s throughput.
- Lead design and architecture for new features and scale-ups. Write design docs, weigh trade-offs across throughput, cost and reliability, and drive decisions with partner teams.
- Mentor teammates through code reviews, design reviews and pairing, and help raise the team’s engineering standards.
- Own your services in production: observability, on-call, incident response and performance tuning.
- Work with product and other engineering teams to turn customer needs into well-scoped technical work.
This role requires
- 8+ years of software engineering experience, including 4+ years building distributed, high-throughput data systems (streaming or batch pipelines).
- Strong production experience in Go and/or Java, and willingness to work in both.
- A solid grounding in distributed systems: partitioning, backpressure, delivery guarantees, failure handling and consistency trade-offs.
- Hands-on experience with Kafka (or an equivalent such as Kinesis or Pulsar), Kubernetes, and a major cloud provider (AWS preferred).
- Experience designing and owning services from design doc through rollout and operation.
- Experience mentoring engineers and leading technical decisions.