Corrective action and preventative action (capa) management
Landis+Gyr is a global leader in energy management solutions with a presence in over 30 countries and a strong commitment to sustainability and innovation
Job Summary
Landis+Gyr is a global leader in energy management solutions with a presence in over 30 countries and a strong commitment to sustainability and innovation.
The Sr Manufacturing Quality Engineer will serve as a technical leader, managing quality processes with contract manufacturers and suppliers, and driving corrective actions to ensure product reliability.
Employees at Landis+Gyr receive a comprehensive benefits package including medical, dental, vision coverage, life insurance, 401(k) with company match, paid time off, tuition reimbursement, and other wellness perks.
Matching Summary
Landis+Gyr is a global leader in energy management solutions with a presence in over 30 countries and a strong commitment to sustainability and innovation.
Salary
Base: $85,490 - $121,393 per year; Bonus/Equity: Consideration for annual bonus; Benefits: Medical, dental, vision, life insurance, 401(k) with match, PTO, tuition reimbursement
Skills & Requirements
Must-have
Process and quality leadership
Statistical quality control techniques
Corrective Action and Preventative Action (CAPA) management
Supplier quality evaluation and audits
Manufacturing process knowledge PCBA Molding Stamping
Root cause analysis for mechanical and electrical products
Use of manufacturing quality tools and software
Nice-to-have
Strong problem-solving skills
Leadership of cross-functional teams
Excellent communication skills
Continuous improvement methodologies
Experience with SAP or equivalent ERP
Familiarity with GD&T and IPC-A-610
Ability to manage multiple priorities
Key Requirements
Minimum 5 years manufacturing quality experience
Bachelor's degree in engineering discipline
Six-Sigma Black Belt/Lean Sigma/DFSS preferred
Experience with Lean, Six-Sigma, DMAIC, APQP, PPAP, FMEA, 8D, CAPA
Ability to travel up to 20 percent
Auditor experience
Strong understanding of manufacturing statistics and process control