> Markdown version of [/jobs/ext/4128967-finance-data-platform-manager](https://www.wearedevelopers.com/jobs/ext/4128967-finance-data-platform-manager). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Finance Data Platform Manager - **Company:** Accenture - **Location:** Manchester, UK - **Experience:** Expert - **Salary:** £66,251.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Infrastructure, Data Integration, Python (Programming Language), Oracle (Applications), Azure Machine Learning, SAP (Applications), SQL Databases, Snowflake, Palantir Foundry, Data Management, Databricks - **Published:** October 31, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5947797902 ## About the Role You take ownership and lead from the front. You're a strong client-facing consultant, comfortable with controllers, senior data people and senior technology stakeholders, and you can explain a technical architecture call to a mixed room in terms of what it means for the business. You bring good judgement and structured problem-solving to ambiguous problems in complex organisations, communicate clearly under pressure, and you're known for sound, decisive calls. You lead multidisciplinary teams well. Things that set strong candidates apart: a track record (typically 7+ years) delivering finance data platform work end to end; hands-on experience with one or more modern cloud data platforms, such as Snowflake, Databricks or Palantir Foundry, among others; experience integrating a data platform with an ERP estate such as SAP or Oracle and the close, consolidation and reconciliation tooling around it; depth in enterprise structure, chart-of-accounts and master data design, on ERP programmes as well as platform builds, and in the governance, lineage and data-quality controls behind a trustworthy finance data model; finance analytics and reporting, including semantic and metrics-layer design; exposure to AI-enabled solutions such as predictive forecasting and agentic use cases; familiarity with SQL, APIs and modern data-integration technologies, with some exposure to Python or ML platforms (deep engineering isn't required); and relevant cloud-data, platform or AI certifications, or a professional finance or accounting qualification. If you have most of this and the drive to build the rest, we want to hear from you. Tell us what you'd bring.