Senior Data Engineer, Product

Oura Oura · Consumer · Helsinki, Finland · Data Engineering & Analytics

Senior Data Engineer focused on product data infrastructure, migrating analytics stack to Databricks, and owning longitudinal member journey data models. Role involves building and maintaining data pipelines, ensuring data quality and governance, and collaborating with product and data science teams. Potential for growth into health science analytics and Data Mesh ownership.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. Own data quality and reliability for the product data domain: schema governance, lineage documentation, data contracts, and monitoring.

Skills

Required

  • 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

Nice to have

  • 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.

What the JD emphasized

  • critical given the sensitivity of health and behavioural data