Data Analyst - Reward

Join a leading multinational airline holding company as a Reward Data Analyst!

We are seeking a detail-oriented and delivery-focused Reward Data Analyst to support a major Oracle HCM transformation programme within a global aviation group. This role sits at the intersection of Reward and HR systems, ensuring the accurate migration, validation, and implementation of compensation and job architecture data. You will play a critical role in supporting the successful delivery of a large-scale transformation project, working closely with both Reward stakeholders and HRIS teams.

Contract Details:

• Contract Length: 6 months (with visibility to extend)
• Contract Rate: £450 per day (inside IR35)
• Location: London (hybrid – 3 times per week on-site)

Key Responsibilities:

• Lead reward-specific data preparation, migration, and testing activities across HCM build and deployment phases.
• Act as the key interface between Reward and HRIS teams, ensuring alignment on compensation and job architecture data.
• Support job architecture activities including job title cleansing, job family and level mapping, and pay range validation.
• Execute system testing cycles, identifying defects, data discrepancies, and risks, and driving resolution with stakeholders.
• Perform detailed data validation and scenario-based analysis to ensure accuracy and system readiness.
• Maintain and organise key documentation including job architecture, organisational structures, and reward policies.
• Support stakeholder engagement and change activities by explaining reward impacts and contributing to training and communications.

Key Requirements:

• Proven experience in a Reward Analyst or Reward-focused HRIS role within a large, complex organisation.
• Strong understanding of compensation, salary structures, and job architecture frameworks.
• Experience supporting HRIS implementations or Oracle HCM testing cycles (Oracle HCM highly desirable).
• Advanced Excel skills with the ability to analyse large datasets and identify trends, gaps, and inconsistencies.
• Strong stakeholder management skills with the ability to communicate technical data clearly to non-technical audiences.
• High attention to detail, with a proactive and analytical approach to problem solving and data governance.

Start Date: ASAP