Staff Software Engineer, Observability

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

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 platforms