CFSI & Quality Lead for Nuclear Projects in London

CFSI & Quality Lead for Nuclear Projects in London

London Full-Time 60000 - 75000 Β£ / year (est.) No working from home possible
CWA

At a Glance

  • Tasks: Lead a team ensuring supplier quality for the Sizewell C project.
  • Company: CWA, a leader in nuclear project management.
  • Benefits: Competitive salary, bonus scheme, and robust pension plan.
  • Other info: Enjoy a hybrid working model with travel opportunities across major UK cities.
  • Why this job: Make a significant impact on nuclear projects while leading a dedicated team.
  • Qualifications: Experience in quality management and team leadership required.

The predicted salary is between 60000 - 75000 Β£ per year.

CWA is recruiting a CFSI Manager to oversee supplier quality within the Sizewell C project. This permanent, full-time role offers a hybrid working model with travel required between London, Manchester, and Bristol.

The successful candidate will lead a team of Quality Engineers, ensuring compliance with quality systems and effectively managing risks.

A competitive salary and bonus scheme are included, along with a robust pension plan.

CFSI & Quality Lead for Nuclear Projects in London employer: CWA

CWA is an excellent employer for those seeking a meaningful career in the nuclear sector, offering a dynamic work culture that values collaboration and innovation. With a competitive salary, bonus scheme, and a robust pension plan, employees benefit from a supportive environment that encourages professional growth and development. The hybrid working model allows for flexibility while engaging with key locations such as London, Manchester, and Bristol, making it an attractive opportunity for quality-focused professionals.

CWA

Contact Details:

CWA Recruitment Team

We think you need these skills to ace CFSI & Quality Lead for Nuclear Projects in London

Supplier Quality Management
Quality Systems Compliance
Risk Management
Team Leadership
Project Oversight
Communication Skills
Hybrid Working Model Adaptability