Finance Data Platform Consultant

Career level: Consultant (CL9) |
Location: London / Manchester / Edinburgh |
Practice: Finance Reinvention Partner (Platform Transformation)

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, and this is where you learn to build one. You'll work on the finance data platforms our clients depend on: 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 use.

You'll be hands‑on from the start: modelling data, building and testing the pipelines that feed the platform, and getting the numbers on it to agree with the ledger. You'll grow quickly, on real programmes, alongside people who architect this work for a living.

Working on the finance data platform. Hands‑on experience of a modern cloud data platform (Snowflake, Databricks or Palantir Foundry, or something comparable) and a working grounding in how one is put together: the layers that take data from raw ingestion through a conformed core to the curated sets finance consumes, the data products built on top of them, and the access and security rules around them.

You build and test what the design calls for. You write queries and transformations that are efficient as well as correct, because compute on these platforms is a cost the client pays for, and you can explain why a piece of finance data sits where it does.

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'll build and test the connections into that estate (SAP, Oracle or whatever a client runs) across subledgers and the general ledger, consolidation, close and reconciliation tooling. You work with ETL, ELT and API patterns, with both scheduled batch loads and change‑data‑capture feeds, and you handle the things source systems do in practice: master data that changes underneath you, late postings, restatements and reopened periods.

You take reconciliation seriously. What the platform reports has to agree with what the ledger says, and building the tests and monitoring that prove it is often your job, as is catching a broken feed before it reaches a reporting pack.

Enterprise structure and finance master data. An awareness of how a finance data model reflects 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. The same work runs on ERP programmes, where chart‑of‑accounts and finance master data design are core work streams, so this is capability you can put to use on a platform build and on an ERP implementation alike.

You'll work with in the governance and lineage the design sets, document what you build, and keep a figure in a report traceable back to the transaction behind it.

Analytics and reporting. This is what the platform is there to serve, and a good part of your work will sit here: building management reporting, the datasets behind self‑service analytics, and the semantic and metrics definitions underneath both, so a measure such as margin or cost to serve means the same thing in every report that uses it. You'll build and test those models and reports, check the numbers behind them against the ledger, and work with the finance people who use them on what they need.

AI on the platform. This is where financial data turns into decisions: predictive forecasting, anomaly detection, AI‑generated commentary and agentic workflows among the use cases, along with the…