Quality Engineer III – Battery Manufacturing & Optimization

Panasonic Corporation of North America; De Soto (KS); Presencial; USD 85.000 - 105.000; Jornada completa

Descripción de la vacante

Panasonic Energy in De Soto, Kansas, is seeking a Quality Engineer III to strengthen our manufacturing quality team for the world’s largest lithium-ion battery factory. You will collaborate with Operations, Engineering, and Maintenance to tackle complex quality issues and drive continuous improvement.

The role requires leading process improvements, mentoring junior staff, and applying data-driven problem solving, SPC, and CAPA within a manufacturing setting.

Formación

• Education, Certifications, and Licenses: Required: Bachelor's degree in a technical field.
• Preferred: Master's degree, Six-Sigma Green Belt, ASQ CQE.

Responsabilidades

• Develop, implement, and validate quality standards, procedures, and controls.
• Lead medium-sized quality and process improvement projects with scope and deliverables.
• Mentor junior quality staff and lead cross-functional improvement initiatives.
• Resolve complex quality issues using structured problem-solving and CAPA processes.
• Communicate results to management and stakeholders; generate KPI reports.

Conocimientos

Quality engineering

Lean Six Sigma

Root cause analysis

Data analysis

Python

SQL

CAPA

Mentoring

Cross-functional collaboration

Educación

Bachelor’s degree in Mechanical, Industrial, Electrical, or Manufacturing Engineering, Quality Management, or a related technical field

Master's degree in Engineering, Quality Management, or a related discipline

Herramientas

SPC

DOE

Python

SQL

Descripción del empleo

Panasonic Energy in De Soto, Kansas, is seeking a Quality Engineer III to strengthen our manufacturing quality team for the world’s largest lithium-ion battery factory. You will collaborate with Operations, Engineering, and Maintenance to tackle complex quality issues and drive continuous improvement.

The role requires leading process improvements, mentoring junior staff, and applying data-driven problem solving, SPC, and CAPA within a manufacturing setting.