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Panasonic Energy in De Soto, Kansas, is seeking a Controls Engineering Technician Supervisor to lead a shift-based CET team responsible for maintaining and troubleshooting PLC-based control systems, machine vision, and related manufacturing tech in our battery production facility.
Reporting to the Controls Engineering Manager, you’ll drive real-time production support, equipment recovery, preventive maintenance, and escalation of complex automation issues while leveraging OEE data to improve
Do you want to join a team that's changing the world? Do you have a strong background as a Controls Engineering Technician Supervisor? Then we're looking for you! Put your skills to meaningful use, gain unique experience, and work with world‑class team members with diverse backgrounds and expertise who share the same vision. Join the PECNA team today!
Join us at Panasonic Energy as we expand to De Soto, Kansas, where we’re building the world’s largest lithium‑ion battery factory. This is an exciting opportunity to grow your career while contributing to the future of electric vehicles. As part of our team, you’ll help push the limits of battery technology, enhancing performance and efficiency in sustainable transportation.
Our state‑of‑the‑art facility, just outside the Kansas City Metro, will be a hub for innovation in green energy solutions. If you're passionate about sustainability and eager to contribute to the electric vehicle revolution, we invite you to be part of our dynamic team. Join us and make a meaningful impact on the future of energy and transportation.
The Controls Engineering Technician Supervisor directly supervises and manages a shift‑based team of Controls Engineering Technicians (CET I, II, and III) responsible for supporting the maintenance, troubleshooting, and reliable operation of controls and vision systems within Panasonic’s battery manufacturing operations. Reporting to the Controls Engineering Manager, this role provides frontline leadership for assigned shift operations, overseeing real‑time production support, fault diagnosis, equipment recovery, preventive maintenance activities, and escalation of complex automation issues involving PLC‑based control systems, machine vision systems, robot vision systems, control networks, and related manufacturing technologies. Utilizing OEE data, loss trees, MMS data, team reports, and other operational metrics, the supervisor prioritizes work, allocates resources, monitors performance, and supports continuous improvement efforts to improve equipment reliability, manufacturing efficiency, and product