Quality Enterprise Capability Owner

Caterpillar Caterpillar · Industrial · Mossville, IL +1

This role focuses on developing and deploying quality visibility and predictive capabilities within a manufacturing context, aiming to improve operational excellence. It involves partnering with various teams to embed quality requirements, define best practices, and analyze data for proactive decision-making, with an emphasis on AI integration in quality.

What you'd actually do

  1. Serve as the Quality subject matter expert for Modern Manufacturing, leading the development, deployment, and sustainment of quality visibility and predictive capabilities that support Operational Excellence.
  2. Drive the innovation, creation and implementation of enterprise quality solutions, ensuring scalability and consistency across manufacturing facilities, with an initial focus on Modern Manufacturing pilot sites.
  3. Partner closely with Modern Manufacturing workstream leads, ECOs, and facility teams to embed quality requirements into broader manufacturing capabilities and initiatives.
  4. Lead the definition, deployment, and monitoring of quality best practices, standards, and KPIs, ensuring alignment with the Future of Manufacturing strategy and measurable business impact.
  5. Analyze quality data and trends to identify risks, opportunities, and improvement actions, enabling proactive decision‑making and predictive insights across operations. Champion AI integration and innovation in quality. Drive digital thread connectivity and support Enterprise Data Domains, including the Global Quality domain and Data Council initiatives.

Skills

Required

  • Bachelor’s degree in Engineering (Mechanical, Electrical, Industrial, or related discipline) or equivalent knowledge demonstrated through professional experience.
  • Strategic Thinking: Demonstrated experience leading enterprise‑level quality and manufacturing initiatives aligned to long‑term business objectives. Proven ability to interpret complex data, market trends, and operational insights to shape strategy and prioritize capability development. Experience positioning organizations for long‑term competitiveness by aligning quality initiatives with the Future of Manufacturing strategy and broader operational goals.
  • Decision Making and Critical Thinking: Extensive experience applying data‑driven decision‑making to complex, ambiguous quality and manufacturing challenges. Proven ability to evaluate assumptions, assess risks, and analyze alternatives to drive sound, high‑impact decisions. Skilled at advising leaders and teams by synthesizing data and applying appropriate decision‑making approaches to deliver sustainable outcomes.
  • Influencing: Proven ability to influence cross‑functional stakeholders and drive alignment across ECOs, workstreams, and manufacturing facilities without direct authority. Experience presenting clear, compelling business cases that address cost, risk, and operational impact. Demonstrates strong capability building buy‑in, commitment, and shared accountability to ensure adoption of quality capabilities and standards.
  • Problem Solving: Extensive experience leading the resolution of complex, high‑impact quality and process problems across manufacturing environments. Skilled in applying structured problem‑solving methodologies, capturing lessons learned, and standardizing approaches to prevent recurrence. Proven success delivering effective, scalable solutions that improve quality performance and operational outcomes.

Nice to have

  • Experience with factory automation and inspection systems
  • Background in visual inspection technologies and AI‑based system implementation
  • Knowledge of process control and advanced manufacturing quality capabilities

What the JD emphasized

  • quality visibility and predictive capabilities
  • Modern Manufacturing pilot facilities
  • Future of Manufacturing strategy
  • quality best practices, standards, and KPIs
  • proactive decision‑making and predictive insights
  • AI integration and innovation in quality
  • quality considerations are integrated early
  • continuous improvement, data‑driven quality management, and operational discipline
  • factory automation
  • inspection systems
  • visual inspection technologies
  • AI‑based system implementation
  • process control
  • advanced manufacturing quality capabilities