Staff Software Engineer, Observability

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We're seeking an exceptional Staff Software Engineer to join our Observability team at Pinterest. This role combines deep technical expertise in distributed systems and data engineering with a product-oriented mindset to build world-class observability solutions that empower our engineering organization. As a Staff Engineer on the Observability team, you'll be responsible for designing and building the infrastructure and tools that provide visibility into Pinterest's large-scale distributed systems, helping thousands of engineers understand, debug, and optimize their services.

• →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

• 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

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. 

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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