Finance Data Engineer - Revenue, LTV & Scorecard

Ōura; San Francisco (CA); Hybrid; USD 172,550 - 203,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Mental health resources

Equity

Oura Ring

Employee discounts

Paid time off

13 holidays

Wellness time off

Job summary

Oura is seeking a Data Engineer – Finance to own the data infrastructure powering financial data such as revenue, LTV, and RevOps. You’ll collaborate with Finance, Sales Ops, and BI to deliver scalable data models and a reliable data layer, while enabling self-serve analytics for leadership.

The role is hybrid and based in San Francisco, CA, with onsite work 1–2 days per week. Strong SQL, Python, and AWS experience are essential.

Qualifications

• 5+ years of experience in data engineering or analytics engineering in production environments.
• Deep experience with financial or revenue data systems.
• Strong SQL and Python skills with reliable data pipelines.
• Experience integrating data from ERP/CRM/e‑commerce platforms (NetSuite, Salesforce, Shopify).
• Familiarity with dbt, Databricks, Spark, or modern lakehouse tools.
• Experience running and monitoring production pipelines on AWS.

Responsibilities

• Design, build, and maintain data pipelines and models for revenue reporting, LTV, and RevOps.
• Partner with Finance, Sales Ops, and BI to translate requirements into scalable data models.
• Own end‑to‑end data quality for financial datasets from ingestion to consumption.
• Integrate data across finance source systems into a unified data layer.
• Ensure compliance, audit, and privacy requirements for financial data.
• Reduce manual reporting by automating trusted, self‑serve data products.

Skills

SQL

Python

Data pipelines

Databricks

dbt

Spark

AWS

NetSuite

Salesforce

Shopify

Tools

Pigment

Looker

Shopify

NetSuite

Job description

Oura is seeking a Data Engineer – Finance to own the data infrastructure powering financial data such as revenue, LTV, and RevOps. You’ll collaborate with Finance, Sales Ops, and BI to deliver scalable data models and a reliable data layer, while enabling self-serve analytics for leadership.

The role is hybrid and based in San Francisco, CA, with onsite work 1–2 days per week. Strong SQL, Python, and AWS experience are essential.