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# Senior Product Owner, Finance Data

- **Company:** Mews
- **Location:** Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Continuous Integration, Information Engineering, Data Governance, Data Systems, Data Streaming, Technical Debt, Data Pipelines, Databricks
- **Published:** May 16, 2026
- **Apply:** https://es.indeed.com/viewjob?jk=d8670b9dfae778ad

## About the Role

Do you have experience in Slack?, * 3+ years in product ownership or product management, specifically in data, platform, or internal tooling environments. You know what good looks like in data-heavy product work.

 * Technical fluency in data engineering concepts: pipelines, dbt, Databricks (or similar), CI/CD, data modelling, testing. You don't need to write the code, but you need to engage credibly with the people who do.
 * Strong instincts for data governance, auditability, and quality. You understand that finance data is different and must be governed accordingly.
 * Experience operating in complex, ambiguous environments where priorities are contested, stakeholders are many, and you need to bring structure without waiting for someone else to provide it.
 * A track record of improving product and delivery maturity from an early baseline, building the intake, shaping, and prioritisation muscles a team needs to scale.
 * Confident communicating trade-offs, capacity constraints, and sequencing decisions to senior finance and technical stakeholders as a peer.
 * Experience in finance data, ERP-adjacent ecosystems, billing/settlement, or complex internal data landscapes is a strong plus.
 * No formal degree required. Equivalent experience in product, data, or finance systems is what counts.

## Description

* Own the product strategy, backlog, and roadmap for Finance Data, covering everything from data pipelines and dbt models to reporting foundations, billing/settlement data flows, and platform governance.
 * Shape messy, cross-functional demand into clear problem statements, trade-offs, and delivery-ready scope.
 * Make prioritisation calls across operational run-support, technical debt, compliance, and new strategic delivery, and communicate the "why" clearly.
 * Protect engineering focus by improving intake, reducing reactive noise, and raising the bar on how work enters the team.
 * Partner with Analytics Engineers, Data Scientists, Finance, FP&A, Treasury, FinTech, and other stakeholders to deliver data products people actually trust.
 * Drive governance, data quality, lineage, and auditability standards across finance-critical data systems.
 * Lead cross-functional conversations where ownership, scope, or the path forward isn't obvious, and bring clarity.


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