P
Staff Software Engineer (Observability)
Skills
Data EngineeringPythonGolangJavaKafkaGrafanaMachine LearningScalaPrometheusKubernetes
25 days ago
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Important information
Contract type:
Permanent
Salary:
$177,185 – $364,795 / year
Location:
San Francisco, CA, USA
Work mode:
Onsite
Published on:
25 September 2026
What they need
- 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- Experience with machine learning or anomaly detection applied to observability use cases
- 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
- Track record of driving adoption of internal platforms through excellent documentation, UX, and developer advocacy
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience
- Contributions to open-source observability projects, a plus
- 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
- Familiarity with cloud-native architectures and technologies (Kubernetes, service mesh, etc.)
- Systems Thinking: Ability to see the big picture while managing complex technical details, balancing trade-offs between cost, performance, and reliability
- Programming Proficiency: Expert-level coding skills in languages like Java, Python, Go, or Scala with ability to write production-quality code
- Distributed Systems Expertise: 7+ years of experience designing and operating large-scale distributed systems with deep understanding of consistency, availability, scalability, and failure modes
- Strong communication skills with ability to influence stakeholders at all levels
- Experience building observability platforms from the ground up or significantly scaling existing solutions
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