Negotiable
Undetermined
Hybrid
Leicester, England, United Kingdom
Summary: The Rewards Manager role involves overseeing reward strategies for a global client based in Leicester, requiring two days in the office each week. The position is a three-month contract focused on managing pay structures, job evaluations, and benefits administration within a complex environment. Candidates should possess strong analytical skills to derive insights from data and lead annual reward cycles effectively.
Key Responsibilities:
- Manage and develop reward frameworks and strategies.
- Lead annual reward cycles and ensure effective implementation.
- Conduct job evaluations and market benchmarking.
- Administer benefits and pay structures.
- Analyze data to provide actionable insights and recommendations.
Key Skills:
- Experience in a reward-focused role, preferably in a multi-site or manufacturing setting.
- Strong technical knowledge of pay structures and job evaluation.
- Proven capability in market benchmarking and benefits administration.
- Highly analytical with data interpretation skills.
Salary (Rate): undetermined
City: Leicester
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: Other
One of our global clients is looking for a Rewards Manager based Leicester- 2 days to office. If you are available and interested in this opportunity, please reply with your latest CV and best available time to discuss this. Below is the job specs for your reference.
Job Title: Rewards Manager
Location: Leicester (2 days a week)
Duration: 3 months contract
Essential Experience: Demonstrated experience in a reward-focused role, preferably within a complex, multi-site or manufacturing setting. Strong technical knowledge across pay structures, job evaluation, market benchmarking, and benefits administration. Proven capability in leading annual reward cycles and developing effective reward frameworks. Highly analytical, with the ability to convert data into clear insights and actionable recommendations.