Staff Software Engineer building and scaling Pinterest's observability platform (metrics, logs, traces) for massive distributed systems. Requires 7+ years distributed systems experience, strong data engineering skills, and expertise with modern observability tools.
177k – 365k
Remote7+ YOEDevOps / SRE
About the role
What you'll do
Define and execute the observability roadmap, treating it as a product. Understand engineering team needs and translate them into technical solutions with measurable impact
Architect, build, and scale distributed observability infrastructure (metrics, logs, traces) to handle massive volumes across Pinterest's distributed systems
Build high-performance data pipelines and storage for real-time and historical telemetry analysis at Pinterest scale
Champion Best Practices: Establish observability standards and patterns across the organization, making it easy for teams to instrument their services and gain actionable insights
Technical Leadership: Mentor engineers, lead architectural reviews, and influence technical decisions across teams to improve overall system reliability and performance
Cross-functional Collaboration: Partner with SRE, Infrastructure, Product Engineering, and other teams to understand pain points and deliver solutions that improve developer productivity and system reliability
Innovation: Stay current with observability trends and technologies, evaluating and adopting cutting-edge tools and techniques to keep Pinterest at the forefront
What we're looking for
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience
Product Mindset: Demonstrated ability to work backwards from customer needs—understanding user needs, prioritizing features, measuring success, and iterating based on feedback. Experience building internal platforms or tools with strong adoption
Distributed Systems Expertise: 7+ years of experience designing and operating large-scale distributed systems with deep understanding of consistency, availability, scalability, and failure modes
Data Engineering Skills: Strong background in building data pipelines, working with time-series databases, columnar storage, stream processing (Kafka, Flink, etc.), and data modeling at scale
Observability Domain Knowledge: Hands-on experience with modern observability tools and practices including metrics, logging, tracing, and profiling. Familiarity with OpenTelemetry, Prometheus, Grafana, or similar technologies
Programming Proficiency: Expert-level coding skills in languages like Java, Python, Go, or Scala with ability to write production-quality code
Systems Thinking: Ability to see the big picture while managing complex technical details, balancing trade-offs between cost, performance, and reliability
Experience building observability platforms from the ground up or significantly scaling existing solutions
Familiarity with cloud-native architectures and technologies (Kubernetes, service mesh, etc.)
Track record of driving adoption of internal platforms through excellent documentation, UX, and developer advocacy
Experience with machine learning or anomaly detection applied to observability use cases
Strong communication skills with ability to influence stakeholders at all levels
Contributions to open-source observability projects, a plus
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