Senior Data Engineer - Finance

We are looking for a Data Engineer – Finance to join our Data Engineering & Analytics team. Your primary focus will be building and owning the data infrastructure that powers Oura's financial data — including revenue, LTV, Corporate Scorecard, and RevOps — ensuring clean, reliable, and timely data for stakeholders across Finance, Sales, and Leadership. While Finance data engineering is your core domain, we expect and actively support our engineers growing into adjacent areas — such as membership, supply chain, or broader platform work — as business needs and individual interests evolve.

This is a hybrid role based in San Francisco, CA, working onsite 1–2 days per week.

- Design, build, and maintain data pipelines and models that power Oura's Corporate Scorecard, revenue reporting, LTV analysis, and RevOps workflows.

- Partner closely with Finance, Sales Operations, and Business Intelligence to understand reporting requirements and translate them into scalable data models.

- Own end-to-end data quality and reliability for financial datasets — from ingestion to consumption-ready tables.

- Integrate and rationalize data across finance source systems (e.g., NetSuite, Salesforce, Pigment, e-commerce platforms) into a unified, governed data layer.

- Ensure financial data pipelines meet compliance, audit, and privacy requirements.

- Reduce manual, spreadsheet-driven reporting processes by automating trusted, self-serve data products.

- Contribute to broader lakehouse architecture work including Apache Iceberg, Databricks, and dbt.

- Expand into adjacent domains such as Membership, RevOps, or Supply Chain data as the team grows.

- Participate in Data Mesh domain ownership design for the Finance domain.

- 5+ years of experience in data engineering or analytics engineering in production environments.

- Deep experience with financial or revenue data systems — understanding of metrics like LTV, ARR, churn, and funnel analytics.

- Strong SQL and Python skills with a track record of building tested, reliable data pipelines.

- Experience integrating data from ERP, CRM, or e-commerce platforms (NetSuite, Salesforce, Shopify, or similar).

- Familiarity with dbt, Databricks, Spark, or modern lakehouse tools.

- Experience running and monitoring production pipelines on AWS or equivalent cloud.

- Ability to work collaboratively with Finance and non-technical stakeholders to define data requirements.

- Self-motivated, pragmatic, and able to manage your own work independently.

- Experience building or owning a Corporate Scorecard or executive-facing metrics layer.

- Familiarity with Pigment, Looker, or similar financial planning/BI tools.

- Experience with Data Mesh and domain-oriented data ownership.

- Exposure to SDM (Supply & Demand Management) or inventory data.