Finance Data Specialist

The Finance Data Specialist owns the organisation's finance data, planning and reporting platforms. The role develops and administers the IBM Planning Analytics (TM1) environment, builds and maintains Power BI reporting, and acts as the finance data owner for the curated datasets in Databricks that underpin both.

Working within the Finance and Data Platforms team and partnering closely with Financial Planning & Analysis, Accounting and the Data team, the role ensures that finance data is accurate, well-governed, reconcilable to source systems and delivered in a form that supports planning, reporting and decision-making.

The successful candidate combines hands-on technical capability in TM1 and Power BI, strong SQL and data modelling skills, and a solid understanding of finance data, processes and reporting requirements.

Planning Analytics (TM1) Development & Administration

Design, develop and maintain TM1 models supporting budgeting, forecasting, consolidation and management reporting, including cubes, dimensions, hierarchies, attributes, rules and feeders.  

Build and maintain TurboIntegrator (TI) processes and chores for data loads, model maintenance and automation.  

Administer the Planning Analytics environment, including security, server and instance configuration, backups, performance tuning and version upgrades.  

Develop and maintain Planning Analytics Workspace (PAW) books and views, and support Planning Analytics for Excel (PAfE) users.  

Support planning and forecasting cycles, including cycle set-up, data preparation, model changes and issue resolution during critical periods.  

Maintain model documentation and ensure changes follow development, testing and release controls.

Power BI Development

Design, build and maintain Power BI semantic models, reports and dashboards for financial and management reporting. 

Develop robust data models using Power Query (M) and DAX, following best practice for star-schema design, performance and reusability.  

Implement and maintain row-level security, workspace structure, deployment pipelines, refresh schedules and gateways.  

Work with Finance stakeholders to gather reporting requirements and translate them into intuitive, reliable reporting solutions. 

Promote self-service reporting through certified datasets, clear documentation and user training.

Finance Data Management (Databricks)

Act as the finance data owner and subject-matter expert for finance datasets in Databricks, defining how finance data should be structured, related and presented for planning and reporting.  

Partner with the Data team, who own ingestion and data engineering, by providing clear requirements, business logic and data definitions for new and changing finance datasets.  

Develop and maintain SQL views and finance-specific models in the curated (reporting) layer that feed TM1 and Power BI. 

Validate new and changed datasets before they are used for reporting, and monitor the ongoing completeness and timeliness of finance data.  

Define access requirements for sensitive finance data and work with the Data team to apply them through Unity Catalog.

Data Quality, Integration & Reconciliation

Own the flow of finance data between source systems, Databricks, TM1 and Power BI, ensuring a consistent, single source of truth.  

Design and maintain reconciliation and data quality checks so that reported and planning data ties back to the general ledger and source systems.  

Maintain finance master data and mappings, including chart of accounts, entities, cost centres, products and other reporting hierarchies, across platforms.  

Investigate and resolve data discrepancies, working with system owners and Finance users.

Documentation, Support & Continuous Improvement

Maintain clear documentation of TM1 and Power BI models, finance business logic, data definitions and data lineage.  

Provide support and training to Finance users of TM1 and Power BI.  

Proactively identify opportunities to automate manual reporting and data preparation, improve performance and simplify the finance data landscape.  

Stay current with developments in Planning Analytics, Power BI / Fabric and Databricks, and recommend improvements.

Project Delivery

Contribute to finance systems and data projects, including new entity onboarding, planning model redesign, reporting uplift and new data sources.  

Work with vendors and partners to ensure deliverables meet requirements and quality standards.