Data Analyst – Finance Transformation Programme

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• Define required finance data attributes, field definitions, and dataset requirements to support reporting, reconciliations, and downstream journal creation.
• Analyse and document source-to-target mappings so that finance data is aligned to agreed structures, Workday‑required values, and reporting needs.
• Support data ingestion activities by validating incoming datasets, checking completeness, and confirming that records are fit for downstream processing.
• Design and execute reconciliation logic across source data, outputs, Prism datasets, Accounting Centre outputs, and reporting results.
• Identify data quality issues, investigate root causes, and work with business and technical teams to improve data accuracy and control effectiveness.
• Define point‑in‑time and snapshot requirements so period reporting remains traceable, explainable, and auditable over time.
• Prepare analytics‑ready datasets and report specifications for Workday and approved downstream reporting tools.
• Produce validation evidence to support SIT, UAT, production readiness, and ongoing finance control requirements.
• Look at historical data to check its fit for the rules in Financial & Actuarial (F&A) module.
• Analyse and document finance data structures and reporting requirements, maintaining robust data lineage and controls.

• Create Source-to-target mapping documents and field‑level data definitions for the finance data stream.
• Create data contracts and dataset specifications aligned to Actuarial, Ceded, F&A, Prism and reporting requirements.
• Create data quality rules, validation outputs, and issue logs showing how completeness, validity, and consistency are assessed.
• Create reconciliation and validation requirements covering Source to F&A, F&A to Ceded, Ceded to F&A, F&A to Actuarial, Actuarial to F&A, F&A to Prism and report to general ledger checks.
• Develop snapshot and history‑tracking requirements to support point‑in‑time reporting and audit traceability.
• Assist with creating test scripts, evidence and production readiness artefacts supporting SIT, UAT, and business sign‑off to “Go Live”.
• Takes responsibility for their own and colleagues’ Health & Safety at all times.
• To ensure customers are treated fairly at all times, in accordance with the Conduct Risk Policy and other relevant policies and procedures.
• To be aware and adhere to all obligations under GDPR, ensuring that the business complies with these requirements.

• KPI:
  Source‑to‑target mappings and data definitions are complete, accurate, and approved, enabling successful downstream processing, minimal defects, and full audit traceability.
• KPI:
  Contracts and dataset specifications are defined, agreed, and maintained, ensuring alignment with business requirements and no critical post‑go‑live issues.
• KPI:
  Controls are established and effective, with high data accuracy and timely resolution of issues in line with agreed standards.
• KPI:
  Reconciliation processes are defined and operating effectively, with minimal variances and timely investigation and resolution of exceptions.
• KPI:
  Data retention and history tracking are in place, enabling reliable point‑in‑time reporting and compliance with audit requirements.
• KPI:
  Testing artefacts are delivered to a high standard, supporting successful test outcomes and readiness for deployment with no data‑related blockers.

• Proven experience in data analysis, finance data transformation, reconciliation, or analytics delivery within finance, ERP, or enterprise reporting programmes.
• Strong capability in data mapping, validation, reconciliation, and audit traceability across multi‑system data environments.
• Good understanding of finance data structures, controls, reporting…