Senior Data Engineer – Hardware & Supply Chain

Hybrid San Francisco, United StatesHybrid

Responsibilities

- Design, build, and maintain data pipelines that ingest and process manufacturing data from Oura's hardware production processes — including device yield, assembly, traceability, and supply chain events.
- Build data models that give Operations, Hardware, and Supply Chain teams reliable, timely visibility into production performance and supply health.
- Own end-to-end data quality and reliability for Hardware/SC data — from factory ingestion to analytics-ready tables.
- Ensure manufacturing data systems meet security, compliance, and data governance requirements.
- Support the Data Mesh initiative by establishing HW/SC as an owned data domain.

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.
- Contribute to broader lakehouse architecture using Apache Iceberg, Databricks, and dbt.
experience in data engineering, with exposure to manufacturing, operations, or supply chain data.
- Strong SQL and Python skills with a track record of building reliable production pipelines. -
Experience integrating data from manufacturing systems — MES, ERP (e.g., SAP, Oracle), factory IoT, or supply chain platforms.
Experience running production data systems on AWS or equivalent cloud.
- Ability to collaborate effectively with Hardware and Operations stakeholders who may not have a data background.
experience with hardware manufacturing data at a consumer electronics or IoT company. -
Experience with device traceability, serialized manufacturing, or supply chain event modeling.
- Familiarity with Databricks, Apache Iceberg, or dbt.

- Competitive salary and equity packages
- Health, dental, vision insurance, and mental health resources
- An Oura Ring of your own plus employee discounts for friends & family
- 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
- Paid sick leave and parental leave
Region 1 $172,550- $203,000
Region 2 $158,950- $187,000
Region 3 $147,900- $174,000
We will never ask for personal information or payment upfront.
Individuals seeking employment at Oura are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by

Our mission at Oura is to empower every person to own their inner potential.
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.
Your primary focus will be building the data infrastructure that powers Oura's hardware manufacturing operations — including production yield, device traceability, quality metrics, and supply chain data.
Oura's hardware data is growing rapidly and is currently supported by a single engineer, creating significant risk and limiting our ability to scale.
While HW/SC Manufacturing data engineering is your core domain, we expect and actively support team members growing into adjacent areas — such as quality testing analytics, firmware data, or broader platform engineering — as the team evolves. What you will do:
Primary Focus – Hardware & Manufacturing Data Engineering
- Integrate data from manufacturing execution systems (MES), ERP/supply chain platforms, and factory data sources into Oura's lakehouse.
- Partner closely with Hardware Engineering, Operations, and Quality teams to understand data needs and deliver scalable data products.