Finance Data Platform Manager 

Career level: Manager (CL7)  |  Location: London / Manchester / Edinburgh  Practice: Finance Reinvention Partner (Platform Transformation) 

Why this role 

Finance has always run on data infrastructure of some kind, but the modern data platform matters more to a finance function than it ever has. This role is for the person who designs that platform for a client's finance function: a governed foundation that holds the enterprise's financial data, integrates with the ERP estate producing it, and carries the reporting, analytics and AI the CFO's teams depend on. You'll own that design in front of the client, from the first architecture decisions through to a platform finance trusts its numbers to. You'll build real credibility across finance, data and AI on marquee programmes, alongside people who architect this work for a living. 

Accenture is a leading solutions and services company. Our strategy is to be the reinvention partner of choice for our clients and lead in the safe, widespread adoption of AI. We bring together our people, deep industry expertise and technology to deliver end-to-end outcomes for clients — and Finance is one of seven Reinvention Partners at the centre of that. Finance RP brings the CFO agenda to life for clients — stronger performance, sharper insight, and better control. 

"As AI reshapes every industry, our clients want a partner that can help them reinvent—boldly, continuously and at speed. Our Reinvention Services leaders bring together the full breadth of Accenture to create solutions to our clients' most complex problems and deliver more value faster, while continuously building the most client-focused, AI-enabled great place to work for our people—our Reinventors." — Julie Sweet, Chair and CEO 

What you'll bring 

The finance data platform. You design the platform itself: the layers that carry data from raw ingestion through a conformed core to the curated sets finance consumes, the data products built on them with named owners and defined quality expectations, and the access, security and governance standards that make it a foundation finance can rely on rather than another copy of the data. You'll work across the platforms clients are standardising on, Snowflake, Databricks and Palantir Foundry among them, and you can lead the selection and architecture calls between those and comparable cloud data platforms. You keep cost and performance under control, because compute and storage are a running cost the CFO will ask you to justify. 

Integration with the ERP estate. Financial data originates in the ERP and the applications around it, and the integration is where most of the difficulty sits. You design how the platform connects to that estate (SAP, Oracle or whatever a client runs) across subledgers and the general ledger, consolidation, close and reconciliation tooling. You set the pipeline design across ETL, ELT and API patterns, and you know when finance is served by a scheduled batch load and when it needs change-data capture or a streaming feed. You design for what source systems do in practice: master data that changes underneath you, late postings, restatements and reopened periods. The data-quality tests and monitoring you put in place catch a broken feed before it reaches a reporting pack, and you hold the line on reconciliation: what the platform reports has to agree with the ledger. 

Enterprise structure and finance master data. You know how a finance data model has to reflect the legal, management and reporting structure of the enterprise: chart of accounts, entities and ledgers, cost and profit centre hierarchies, and the finance master data underneath them. That design work is as much at home on an ERP programme as on a platform build, since chart-of-accounts and master data design are core workstreams on any finance ERP implementation, and the role is meant to be deployable on both. You design the governance, ownership and lineage around it, so a figure in a report traces back to the transaction behind it and the platform stands up to the controls and audit scrutiny finance is held to. 

Analytics and reporting. This is what the platform is built to serve, and where much of the value is realised. You design the reporting and analytics layer on top of it: management reporting, and self-service analytics for finance teams who want to answer their own questions. Underneath both sits the semantic and metrics layer, where a measure such as margin or cost to serve is defined once and means the same thing in every dashboard and model that calls it. You make performance analysis work off governed platform data instead of a spreadsheet chain, from budget and forecast variance to driver analysis and profitability, and you design it for the finance people who will use it. 

AI on the platform. This is where financial data turns into decisions: predictive forecasting, anomaly detection, AI-generated commentary and agentic workflows, with the human-in-the-loop controls that keep finance in charge of what the models produce. There is every opportunity to be part of those conversations and to help design the models and agents behind them. If you know how to move a client from isolated experiments to governed, explainable capability, that counts for a lot, and you can direct the data scientists and AI engineers who build it without needing to be one yourself. 

Leading the design. You lead design workstreams in front of the client, from discovery and architecture through to the design decisions that carry into deployment, adoption and hypercare. You act as the design authority for the finance data platform, holding the solution to what finance needs for control, reconciliation and auditability, and you keep senior finance, technology and data stakeholders aligned through design reviews and honest conversations about trade-offs. There is plenty of scope to get into design and deployment tasks alongside the team, and you stay close enough to review a data model, a pipeline or a report yourself. 

Growing the work. You work day to day alongside senior people in the client's finance, data and technology teams, and you pick up the signals and pain points that point to work worth doing next. You lean into them. You help build the reusable assets and points of view that make the next programme better than the last, and you develop the people around you. 

Ways of working. We're increasingly an AI-first delivery team, bringing agentic tooling and orchestration into how we design, analyse and deliver, with our people owning the judgement and the outcome. If you already work this way, that's a real plus, and we're keen to hear from people bringing that experience.