End-to-End Warranty Throughput Lead

Ford; Dearborn (MI); Presencial; USD 72.000 - 129.000; Jornada completa

Descripción de la vacante

Ford Dearborn is seeking an experienced Warranty/Quality Analyst to lead problem solving throughput and aging delivery across multiple vehicle functions. You will drive the SAQ-based priority setting, coordinate with VFGs and PQ engineers, and ensure robust problem solving across the program lifecycle.

You will leverage quality tools, problem-solving methodologies, and data analytics to shape proactive quality planning and learnings for future programs.

Formación

• Bachelor's Degree in Engineering, Sciences, or academic equivalent.
• Working knowledge of Ford's quality tools and process.
• Working knowledge of Problem-Solving Methodology (e.g., Global 8D, PDCA).
• Green Belt certification required.
• Demonstration of strong collaboration capabilities, with abilities to pull together teams to work towards a common outcome.

Responsabilidades

• Own delivery of throughput status and aging for functional units, collaborating with teams to gather, analyze, and drive problem solving.
• Monitor aging targets and ensure focus on prioritized work, accelerating where needed to avoid breaches.
• Ensure SAQ issues are properly scoped and priorities address business needs.
• Cascade forward-model-responsible cases through PCA and PRA processes.
• Collaborate with PQ, engineering, manufacturing, service, and supplier quality teams for alignment.

Conocimientos

Problem solving

Collaboration

Data analysis

Quality mindset

Educación

Bachelor's Degree in Engineering/Sciences

Master's Degree preferred

Herramientas

Ford quality tools

Descripción del empleo

Ford Dearborn is seeking an experienced Warranty/Quality Analyst to lead problem solving throughput and aging delivery across multiple vehicle functions. You will drive the SAQ-based priority setting, coordinate with VFGs and PQ engineers, and ensure robust problem solving across the program lifecycle.

You will leverage quality tools, problem-solving methodologies, and data analytics to shape proactive quality planning and learnings for future programs.