Senior Data Engineer, Product

We are looking for a Senior Data Engineer – Product to join our Data Engineering & Analytics team, based in Helsinki. Your primary focus will be the software product data domain — owning the data infrastructure that powers Oura's end-to-end longitudinal member journey, spanning member engagement, health intelligence, and personalized product experiences. A major part of this role is maturing our product analytics stack from its current foundation (Amplitude, Segment, Snowflake, Athena, QuickSight) to a unified, governed Databricks-based platform. While product data engineering is your core domain, we expect and actively support team members growing into adjacent areas — such as health science analytics, platform infrastructure, or data mesh ownership — as the team and business evolve.

This role is based in Helsinki, Finland.

• Design, build, and maintain data pipelines that unify Oura's product and member behavioural data — including engagement events, feature usage, session data, health intelligence signals, and subscription lifecycle — into a reliable, governed data layer.
• Lead the migration of product analytics infrastructure from the current stack (Amplitude, Segment, Snowflake, Athena, QuickSight) to Databricks, ensuring continuity of existing analytics while dramatically improving scalability, governance, and cost efficiency.
• Build and own the end-to-end longitudinal member journey data model — a unified view of how members engage with Oura's app and ring across health intelligence features, wellness journeys, and subscription milestones.
• Partner closely with Product, Data Science, and Health Intelligence teams to define data requirements and deliver pipelines and models that power product decisions at scale.
• Own data quality and reliability for the product data domain: schema governance, lineage documentation, data contracts, and monitoring.
• Ensure product data systems comply with Oura's privacy, data governance, and security requirements — critical given the sensitivity of health and behavioural data.
• Evaluate and rationalise the existing tool stack — instrument Segment event schemas, manage Amplitude data exports, maintain Snowflake/Athena integrations during transition — and progressively consolidate onto Databricks.
• Write clean, tested, production-grade code primarily in Python and SQL.

• Contribute to the broader Databricks lakehouse architecture (Apache Iceberg, dbt, Unity Catalog).
• Expand data engineering coverage to Health Intelligence and Science data domains.
• Support the Data Mesh initiative by establishing Product as an owned, well-governed data domain.
• Mentor and collaborate with analysts who consume product data.

• 5+ years of experience developing and operating production data pipelines.
• Hands-on experience with product analytics stacks — specifically Amplitude, Segment, or equivalent event-tracking and CDP platforms — and strong intuition for how product behavioural data is structured.
• Experience migrating or consolidating data infrastructure; comfort working in a multi-tool environment during a platform transition.
• Strong SQL and Python skills; track record of building tested, reliable, production-grade pipelines.
• Experience with cloud data warehousing — Snowflake, Athena, BigQuery, or similar.
• Good understanding of event-driven architectures, stream processing, and longitudinal / session-level data modelling.
• Familiarity with dbt, Databricks, Spark, or modern lakehouse tooling.
• Experience running and monitoring production data systems on AWS or equivalent cloud.
• Self-motivated, pragmatic, and able to lead your own work in a distributed team.
• Fluent in English; comfortable collaborating across Finland, the US, and other Oura locations.

• Real-world Databricks experience, including Unity Catalog or Delta Live Tables.
• Experience designing member or user journey data models for a consumer subscription or digital health product.
• Familiarity with health data — wearable telemetry, physiological signals, or clinical/wellness event data.
• Experience with Data Mesh and domain-oriented data ownership.
• Broad knowledge of software fundamentals, system design, and multiple programming languages.