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$172,550 – $203,000
Listed on Oura’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role combines hardware quality engineering with data analytics, focusing on manufacturing and field performance data to identify and prevent product issues. It suits experienced data professionals who want to work with real-world hardware problems and collaborate across manufacturing, engineering, and quality teams.
Our summary, not Oura’s wording. The full posting is on their site.
Skills this role names
- Amazon Web Services (AWS)
- Anomaly Detection
- Databricks
- Dialectical Behavior Therapy (DBT)
- Python
- SQL
- Statistical Process Control (SPC)
- Tableau
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What they ask for
Required
- 5+ years of data work in engineering, manufacturing, quality, reliability, or operations
- Strong SQL skills and hands-on Python for data analysis and automation
- Experience with large datasets and engineering-focused analysis
- Manufacturing, hardware test, reliability, warranty, field, or product data experience
- Working knowledge of statistics, population comparison, correlation identification, and trend evaluation
- Analytics and visualization experience with Tableau, Databricks, or similar tools
- Problem-solving skills and understanding of product and process behavior
- Cross-functional collaboration across Hardware, Manufacturing, Firmware, Quality, Reliability, and Data teams
- Clear communication of technical findings to engineering and leadership
Nice to have
- Consumer electronics, wearables, IoT, or medical device experience
- Manufacturing test data, MES, serialized traceability, or device telemetry experience
- Warranty, RMA, reliability, or field-return data analysis
- Correlating manufacturing or test parameters with downstream failures
- Understanding of hardware test, manufacturing processes, failure mechanisms, battery behavior, or electrical systems
- Statistical process control, anomaly detection, or predictive analytics applied to hardware or manufacturing
- Familiarity with Databricks, Tableau, AWS, dbt, or similar platforms
- AI/ML model validation experience with manufacturing datasets