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Production Supervisor

Johnson Controls

CAN

Full-time

Mid

Onsite

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You will be responsible for supervising and coordinating the activities of production and operation workers (approximately 50-75 employees), such as assemblers, inspectors, precision workers, machine operators, fabricators, and plant and system operators while ensuring that production schedules are created and completed on time, safely, and within budget.
How you will do it
Develop and implement short, medium, and long-term operational plans that align with production requirements and organizational priorities to meet schedule adherence and On‐Time Delivery (OTD) targets.
Manage staffing, time & attendance, and resource allocation to support delivery and throughput.
Diagnose performance gaps (e.g., OTD disruptions), perform root‐cause analysis, and implement sustainable CAPAs.
Champion EHS through proactive safety observations, training, and timely resolution of unsafe conditions/behaviors.
Ensure compliance with applicable quality, customer, and regulatory standards and maintain audit readiness.
Drive continuous improvement using JBS tools (Standard Work, Daily Management, Gemba, 5S, Kaizen) to improve SQDC metrics.
Lead, coach, and develop the team: set expectations, define measurable goals, and build accountability and high performance.

Required:
Bachelor’s or Master’s degree with 5+ years of experience in a manufacturing environment.
Educational background in Manufacturing or Engineering, (e.g., Mechanical, Electrical, Industrial, Manufacturing,) preferred.
Proven leadership experience (min. 3 years) in a supervisory or indirect leadership role.
Strong understanding of end‐to‐end manufacturing operations, including planning, material flow, logistics, and supply chain processes.
Demonstrated ability to lead and develop teams using KPIs, structured performance systems, and data‐driven decision-making.
Proficiency in JBS/Lean tools (e.g., Standard Work, 5S, Kaizen, problem-solving) combined with strong analytical skills and the ability to manage multiple priorities in dynamic environments.

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