Payroll Data Analyst (Global Programme)
Location: Reading or Dublin (hybrid)
Duration: Initial 6 Months
Contract Type: Day Rate (Inside IR35 if UK based)
About the Role
We’re hiring a Payroll Data Analyst to support payroll transformation, system implementations, and operational improvement across a complex, multi‑country organisation. You’ll analyse, validate, cleanse, and reconcile payroll data while working closely with Payroll, HR, Finance, Technology, and external providers to ensure accuracy, integrity, and compliance.
Key Responsibilities
- Payroll data analysis - Analyse, validate, and reconcile data across multiple systems.
- Data cleansing & migration - Support mapping, transformation, QA, and migration activities.
- Transformation support - Contribute to payroll system implementations and process improvements.
- Reporting & insights - Produce dashboards, reports, and actionable insights.
- Issue investigation - Resolve discrepancies and recommend fixes.
- Audit & compliance - Support statutory reporting and audit data needs.
- Controls & documentation - Maintain validation, reconciliation, and control processes.
- Testing support - Assist with UAT and parallel payroll runs during implementations.
Essential Skills
- Proven experience as a Payroll Data Analyst or similar role.
- Strong understanding of payroll processes, data structures, and controls.
- Advanced Excel (Pivot Tables, XLOOKUP, Power Query).
- Experience working with large data sets and complex reconciliations.
- Exposure to payroll system implementations or upgrades.
- Excellent attention to detail, problem‑solving, and stakeholder engagement.
- Experience partnering with Payroll, HR, Finance, and external providers.
Desirable
- Retail or multi‑site experience.
- Knowledge of UK/international payroll.
- Familiarity with systems like Workday, SAP, Oracle, ADP, SD Worx, SuccessFactors.
- Experience with Power BI, SQL, or other visualisation tools.
- Background in payroll migrations or outsourcing programmes.
- Understanding of GDPR and payroll data governance.