Senior Backend Engineer, Context Hub

Our mission at Oura is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles. Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office. The Context Hubis a knowledge store within Oura's HealthOS platform. It ingests data from diverse sources, transforms it through both pipelines and LLM-based interpretation layers, and serves structured User Context. If Oura's intelligence systems are the brain, the Context Hub is the memory. This is an opportunity to be part of teams that are at the forefront of wearable technology, innovating and defining the future of Oura’s products through collaboration across different teams. What You Will DoThis is a platform-building role. You'll design foundational data infrastructure that multiple product teams depend on - not ship features in isolation. Designdata transformation pipelinesthat convert raw health signals, user inputs, and third-party data into structured, queryable contextArchitectevent-driven ingestionusing tools like Kinesis, EventBridge, and SQS - handling duplicate events, traffic spikes, and partial failures gracefullyDefineflexible data models and schemasfor a hierarchical health context ontology that evolves as new context types emergeBuildmulti-consumer APIs and data contractsserving LLM-powered reasoning engines, mobile apps, and analytics pipelines through clean, well-documented interfacesOperate and design data storage at scaleCreateSDKs and integration surfacesthat let other squads contribute and own contexts with minimal frictionCollaborate effectively in a globally distributed, diverse, and cross-functional team, adapting as Oura evolves and new opportunities emerge.Ownproduction qualityend-to-end: testing, monitoring (Grafana, Prometheus, OpenTelemetry), alerting, and documentation How We Build With AIAt Oura, AI is a core part of how we build software. We encourage senior engineers to use tools like Cursor, Claude Code, and GitHub Copilot to accelerate pipeline development, iterate on schema design, prototype integration patterns, and reduce boilerplate - so you can focus on the hard problems. All code is reviewed and owned by the engineer. AI is a multiplier, not a crutch. We're looking for engineers who view AI as a coworker in the development loop, not just autocomplete. Requirements5+ years building and operating production data systems at scale in PythonExperience designing event-driven architectures - message brokers, event streams, CDC pipelines, with understanding of delivery guarantees, fan-out, and backpressureDeep experience with data transformation pipelines - ingesting from heterogeneous sources, normalizing, enriching, and serving with clear data contractsStrong technical grasp of AWS ecosystems with a focus on varied data storage solutions (RDS, DynamoDB, etc.), asynchronous messaging (SQS, EventBridge), and scalable compute environments like EKS and Lambda.A data-model-first mindset - you start with the shape of the data and access patterns before jumping to service architectureExperience building shared platforms or APIs that multiple teams depend on, with thoughtful versioning and self-service integration patternsStrong systems design instincts - you think in terms of data integrity, resilience, and failure modes before they become incidentsExcellent communication - you explain your thinking before acting, ask incisive questions upfront, and articulate trade-offs clearlyHave a team-oriented mindset and enjoy working in a diverse environment with distributed teamsNice to HavesExperience withFastAPIor AWS Lambda PowertoolsBackground in health data, wearables, or familiarity with FHIR/SNOMED/ICDAprivacy-first approachto engineering, with a solid understanding of the best practices for handling sensitive data (PHI/PII).Building infrastructure that feeds data to/from LLM-powered servicesFamiliarity with feature stores, embeddings, or vector databasesExperience in building eff