Oura
Senior Data Analyst, Hardware & Supply Chain
Hybrid - San Francisco, California · Senior
Sponsorship not specified$172k-$203kDetected 20 days ago
PythonGitSQLSnowflakeDatabricksAWSdbtData AnalysisData EngineeringData VisualizationAgentic AIAuditingSupply ChainLogisticsERPHardware DesignUnityLeadershipCommunicationMentoringInternal AuditNetSuite
About the role
- We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.
- 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.
- This is the data behind hardware manufacturing, supply chain, revenue, units sold, COGS, margin, inventory, and the warranty and returns metrics that show up in board and S-1 reporting.
Responsibilities
- Own the analytics layer for the hardware and supply chain scorecard - partner with Operations, Supply Chain, and Finance to define, document, and deliver the KPIs that show up in board and S-1 reporting (hardware revenue, units sold, sell-through, COGS, landed cost, gross margin, on-hand and in-transit inventory, warranty rate, return/RMA rate, and activation rate).
- Establish each hardware/SC KPI as a governed, audit-grade data product - locked definitions, single owner, data build tool (dbt) tests, full lineage from source systems, formal sign-off, and a documented change-management process.
- Build and own the hardware data contract and hardware - the canonical dimension that ties SKUs, components, ring generations, sizes, and finishes to every downstream sales, inventory, and activation metric.
- Build and maintain the Hardware/SC domain's data products in Databricks, mentoring analysts on dimensional modeling, dbt practices, and the Golden Path for publishing governed metrics for reporting and for MCP/agentic AI consumption.
- Partner deeply with Supply Chain and Operations on demand/supply planning data - own the Databricks-side data layer that feeds planning, and ensure planned, reported, and warehouse numbers reconcile across regions.
- Deliver inventory, fulfillment, and supplier analytics - days of supply, fill rate, on-time delivery, yield, scrap, and cost-to-serve - that give Operations leadership a single trusted view.
- Drive adoption of self-service reporting by Operations and business partners - using Genie, Databricks SQL dashboards, and clear documentation to reduce one-off reporting and free up analyst time for analysis.
- Demonstrated experience building executive-level reporting for a physical-product business that is trusted by leadership and survives external scrutiny (Board, auditors, investors).
- Track record of working alongside external auditors (PwC, Deloitte, EY, KPMG) and building documentation that withstands audit review.
- An Oura Ring of your own plus employee discounts for friends & family
Requirements
- Experience standing up a hardware data contract and product/SKU dimension (dim_hardware) from scratch in a high-growth consumer hardware company.
- Expertise in data visualization theory - you understand how to choose the right chart for the right operational message and why exec dashboards fail when they don't.
- We Would Love to Have You on Our Team, If You Have
Nice to have
- Hands-on experience with demand/supply planning data and a real understanding of where the planning system ends and the data lake begins.
- Highly fluent in SQL with experience writing complex queries for operational and financial data extraction, reconciliation, and modeling.
- Expertise in dimensional modeling for hardware/operations reporting (conformed dimensions across SKU, product generation, channel, geo, supplier
- slowly-changing dimensions for product and cost hierarchies
- period-over-period comparisons).
- Experience with dbt - including tests, documentation, exposures, and contracts.
- Experience with Databricks strongly preferred (Unity Catalog, Databricks SQL, Lakeflow, Genie)
- deep Snowflake experience acceptable with willingness to migrate.
Compensation
- Region 1 $172,000- $203,000
- Region 2 $158,950- $187,000
- Region 3 $147,900- $174,000
Benefits
- Everyone here at Oura has a ring of their own, and we are continually looking to improve employee health.
- Competitive salary and equity packages
- Health, dental, vision insurance, and mental health resources
- 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
- Paid sick leave and parental leave
- While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions.
Company info
- Alaska (AK), Delaware (DE), Iowa (IA), Mississippi (MS), Missouri (MO), Nebraska (NE), South Dakota (SD), Vermont (VT), West Virginia (WV), and Wisconsin (WI)
- Oura is proud to be an equal opportunity workplace.
- We celebrate diversity and are committed to creating an inclusive environment for all employees.
- 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 federal, state, or local laws.
- We will not tolerate discrimination or harassment based on any of these characteristics.
- We will work to ensure individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions, and to receive other benefits and privileges of employment.
- What Makes You Stand Out
- At Oura, we care about you and your well-being.
This listing is sourced directly from Oura's careers page and normalized into a canonical job model.