Overview
In this role you will lead a large manufacturing operation at Duxford, ensuring safe, compliant production that meets quality, cost, and delivery targets. You will manage a 50+ person team, drive continuous improvement, and support new product introductions and technology transfers. You will collaborate across planning, maintenance, engineering, and R&D to improve plant performance and growth. This is a hands-on leadership position in a global company known for advanced composites, offering meaningful impact on operations and safety.
Responsibilities
- Lead safe manufacturing operations in compliance with health, safety, and environmental standards
- Deliver quality, cost, and delivery targets through effective production management
- Develop and implement annual production plans aligned with business objectives
- Lead and develop a 50+ person team including supervisors and technical staff
- Ensure products meet customer requirements, quality standards, and delivery schedules
- Drive continuous improvement using Lean, Six Sigma, root cause analysis, and related tools
- Manage manufacturing assets, inventory, and resources to maximise efficiency and control costs
- Support new product introductions, processes, and technology transfers
- Lead quality investigations, resolve non-conformances, promote right-first-time culture
- Collaborate with planning, maintenance, engineering, R&D, and other stakeholders to improve plant performance and support growth
Key requirements
- Degree or equivalent in Chemistry, Chemical Engineering, Engineering or Materials Science
- Experience in manufacturing at supervisory/management level with proven communication skills
- Experience with diverse technologies and ability to manage multiple projects simultaneously
- Ability to set priorities and address problems promptly
- Experience meeting deadlines and working in a team
- Strong planning and leadership skills
- leadership
- communication
- teamwork
- 9 Phase root cause analysis
- Lean Six Sigma
- Process Failure Mode Effects Analysis (PFMEA)
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