Manufacturing Operations Manager

Overview

In this role you will lead Glenrothes plant operations to strengthen competitiveness and ensure safe, quality production at scale. You will work with cross-functional teams to translate prototypes into stable production, manage a sizeable budget, and drive continuous improvement. The position emphasizes lean, quality, and collaboration with unions and HR to sustain a high-performing manufacturing culture. This is a strategic, impact-focused leadership role within a global automation leader.

Pay / Benefits

• employee discounts
• on-site parking
• flexible work-time options
• sports and health opportunities
• various benefits and services
• creative room (room for creativity)

Responsibilities

• Formulate and execute departmental strategic plans to improve plant competitiveness as part of the plant management team
• Oversee daily machining and plant operations for cast and steel components to ISO9001; lead ~100 associates and support staff to meet targets, quality, and safety
• Own the departmental budget, drive cost savings, allocate resources, and support technical investment planning (MFO1/MFE1)
• Collaborate with Design Office and Production Engineering for smooth prototype-to-series transitions and represent Glenrothes in IPN
• Mentor technical teams and apprentices; foster collaboration, safety, accountability; support career progression
• Build and lead a high-performing team focused on operational excellence, quality, efficiency, and productivity

Key requirements

• Degree in Engineering (Mechanical, Manufacturing, or a related technical discipline) or equivalent leadership experience
• Track record managing substantial operational budgets and CapEx (MFO1) in a technical facility
• Knowledge of industrial regulations, facility compliance, and safety standards

• Strong communication and interpersonal skills
• Negotiation with unions and stakeholder management
• Coaching and people development
• Lean manufacturing and continuous improvement (BPS)
• Machining and process optimization; tooling and capacity modelling
• Data analysis for KPI reporting and project management

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