Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google's services—both our internally critical and our externally-visible systems—have reliability, uptime appropriate to users' needs and a fast rate of improvement. Additionally SRE’s will keep an ever-watchful eye on our systems capacity and performance.
Much of our software development focuses on optimizing existing systems, building infrastructure and eliminating work through automation. On the SRE team, you’ll have the opportunity to manage the complex challenges of scale which are unique to Google, while using your expertise in coding, algorithms, complexity analysis and large-scale system design.
SRE's culture of intellectual curiosity, problem solving and openness is key to its success. Our organization brings together people with a wide variety of backgrounds, experiences and perspectives. We encourage them to collaborate, think big and take risks in a blame-free environment. We promote self-direction to work on meaningful projects, while we also strive to create an environment that provides the support and mentorship needed to learn and grow.
To learn more: check out our books on
Site Reliability Engineering or read a
career profile about why a Software Engineer chose to join
SRE.
Geo Data Site Reliability Engineering ensures Google Maps' geographical data integrity. In this role, you will lead a team focused on planetary-scale infrastructure, moving beyond quick patches to re-architect systems, improve data safety, and pilot AI Operations.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about
benefits at Google.
Responsibilities
- Shield engineering project time by reducing operational noise and overseeing the local New York rotation within a multi-site follow-the-sun on-call model.
- Focus on End-to-End Data Journey Reliability by establishing clear Recovery Time Objectives (RTOs) for map data errors with partners like Map the World, treating poor data quality as a binary outage.
- De-risk major architecture evolutions (e.g., Real-Time Data streaming, Hyperfresh Roads) using proactive strategies that correlate user harm with change vectors to automatically pause or revert bad releases globally.
- Serve as the systems engineering authority for Geo's data systems, partnering directly with Director and Vice President developers leads to map dependencies and fix structural flaws preemptively.
- Pilot AI Operations to handle routine toil (drains, basic triage, rollbacks), minimizing on-call tax and shifting focus to forward-looking systems architecture.
Minimum qualifications:
- Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages.
- 5 years of experience managing people.
- 4 years of experience leading projects.
- 3 years of experience in designing, analyzing, and troubleshooting distributed systems.
Preferred qualifications:
- Master's degree in Computer Science or Engineering.
- Experience leading teams managing mission-critical data pipelines, real-time streaming architectures (e.g., Beam, Flink, Pub/Sub, Kafka), or massive batch processing systems.
- Demonstrated success partnering as a peer with Product Engineering Directors and Operation leads to align engineering velocity with production safety standards.
- Track record of defining and defending data-centric reliability models (e.g., semantic data health, data freshness, and data-error RTOs) beyond traditional server uptime and Remote Procedure Call (RPC) latency.