Senior Quality Engineering Manager - Failure Analysis Lead

Hobbsnews; Irvine, Northern (CA, KY); On-site; USD 165,000 - 263,000; Full time

Job summary

BD is seeking a Senior Quality Manager, Failure Analysis in Irvine, CA to lead a team of engineers and technicians. You will drive thorough failure investigations, root-cause analyses, and corrective actions to ensure product reliability and quality across medical devices.

The role requires strong leadership, data analytics expertise, experience with Six Sigma and LEAN methods, and a background in engineering.

Qualifications

• Bachelor's Degree in engineering.
• 8+ years in medical device Failure Analysis and data analytics.
• Quality Engineering/Quality Management, R&D experience.
• Demonstrated management of technical/engineering disciplines.

Responsibilities

• Lead a team of engineers and technicians conducting failure investigations, identifying root causes, and implementing corrective actions.
• Develop failure analysis tools and processes for ongoing root cause analysis and proactive quality improvement.
• Oversee cross-functional project teams and budget considerations as applicable.
• Provide technical guidance to cross-functional groups and integrate design recommendations into product components or processes.
• Lead CAPA program implementation including training, approvals, and system effectiveness.
• Interact with production supervisors, customers, and other stakeholders; present at internal and external meetings.

Skills

Six Sigma Certification

Project Leadership

Data Analysis

Quality Engineering

Root Cause Analysis

Cross-functional Collaboration

Education

Bachelor's Degree in Engineering

Tools

Microsoft Office

Job description

BD is seeking a Senior Quality Manager, Failure Analysis in Irvine, CA to lead a team of engineers and technicians. You will drive thorough failure investigations, root-cause analyses, and corrective actions to ensure product reliability and quality across medical devices.

The role requires strong leadership, data analytics expertise, experience with Six Sigma and LEAN methods, and a background in engineering.