Reliability Engineering Senior Manager

Your work will significantly contribute to the organization's ability to monitor product performance in manufacturing and the field, enhancing overall product reliability. M.S. in an engineering discipline such as Materials Science, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering, or related fields; Ph.

Are you ready to lead a team that drives the successful qualification and commercialization of new technologies?

About the Role

This leadership position is pivotal in ensuring efficient processes and systems are in place for assessing design and process changes. Your work will significantly contribute to the organization's ability to monitor product performance in manufacturing and the field, enhancing overall product reliability.

Key Responsibilities

• Lead the development of systems and activities to assess design and process changes.
• Build reliability modeling infrastructure and develop processes to understand technology and material interactions.
• Manage the implementation and execution of DFMEA and support the development of product qualification plans.
• Generate actionable information through testing and data analysis to improve module reliability.
• Own the training, use, maintenance, and continuous improvement of DFMEA.
• Implement a world-class safety culture and instill a Safety First mentality.
• Develop and lead a team responsible for the qualification of new technologies at the module level.
• Establish cross-functional FMEA-based risk assessments of new designs.
• Develop and execute qualification processes and procedures to limit risk in product release.
• Develop reliability test methods and validate assumptions in the field.
• Communicate process and product reliability concerns cross-functionally.
• Work closely with certification agencies to secure required module certifications.
• Enhance infrastructure for quality, reliability, and material analysis.
• Support global high-volume manufacturing reliability monitoring systems.
• Drive root cause analysis of module performance issues and establish corrective actions.
• Build, lead, motivate, and mentor a highly-talented Reliability Engineering team.

Minimum Requirements

• M.S. in an engineering discipline such as Materials Science, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering, or related fields; Ph.D. preferred.
• 10 years of experience in an engineering discipline, including volume manufacturing and process/product improvement.
• 10 years of experience in reliability prediction modeling, reliability physics, and MTBF.
• 8 years of engineering leadership and management experience in process engineering and/or process development.
• 5 years of experience managing the Quality and/or Reliability function in a global volume manufacturing and product development setting.
• Demonstrated expertise in creating safe work environments.
• Strong technical background with knowledge of advanced manufacturing technologies.
• Proficient in data mining, data analysis, SPC, lean manufacturing concepts, reliability analysis, and six sigma.
• Excellent interpersonal, managerial, organizational, and team-building skills.
• Proficient use of all Microsoft Office suite programs.

Work Environment

• Travel: 5% - 10%

 

At Talent Wave Associates, we connect outstanding talent with exceptional opportunities. We're proud to be an Equal Opportunity Employer and are committed to fostering an inclusive, people-first recruiting experience. Ready to ride the wave of opportunity? Apply today!

As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our applicant tracking system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.

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