TechBiz Global GmbH
Team Lead Assembly(m/w/x)
Vollzeitnur vor OrtSenior
Berlin, Hamburg, München, Köln, Frankfurt am Main, Leipzig, Düsseldorf, Stuttgart, Essen, Dresden
Neuer Job?Nejo!
Dein persönlicher KI-Karriere-Agent
MAMagna
Group Kaizen Leader(m/w/x)
München
VollzeitVor OrtBerufserfahren
AI/ML
Data Science
Nejo KI-Zusammenfassung
Manual and robotic line rebalancing with SMED and A3 problem solving across seating and component plants. 3-5 years of Lean manufacturing experience in multi-plant operations preferred. Support for multi-site travel, varied process stabilization tasks.
Anforderungen
- Degree in Engineering, Operations, or equivalent experience
- 3–5+ years in Lean/CI manufacturing
- Experience supporting multi-plant operations (advantageous)
- Knowledge of Lean methodologies
- Familiarity with component-plant processes
- Proficiency with Power BI, SQL/DAX, and MES
- Basic analytics, AI, and ML skills
- Clear communication, facilitation, and leadership
- Ability to manage priorities and lead change
- Analytical and structured problem-solving mindset
- Flexibility and willingness to travel
- Lean and Kaizen leadership experience
- Flow optimization and pull systems knowledge
- MAFACT and standardized work deployment skills
- Data analytics, AI/ML, and BI tools proficiency
- Welding, stamping, CNC, and foam process familiarity
- Change leadership and coaching skills
Aufgaben
- Lead CI and Kaizen activities across seating and component plants
- Conduct time studies for manual and automated processes
- Rebalance work content for robotic and manual lines
- Facilitate A3 problem solving and root cause analysis
- Perform 5-Why, SMED, and process stabilization activities
- Implement pull systems and Heijunka principles
- Apply flow principles in assembly and component manufacturing
- Optimize production cells and welding lines
- Improve stamping presses and CNC machining centers
- Optimize foam molding and sub-assembly stations
- Reduce changeover times through SMED
- Ensure tool and mold readiness
- Improve material presentation for high-mix environments
- Develop VSMs for upstream and downstream operations
- Create integrated flow maps for JIT seating
- Deploy Standardized Work and visual controls
- Implement TPM, LPA, and stability-building activities
- Support MAFACT audits and global manufacturing standards
- Build Power BI dashboards to track performance
- Monitor OEE, scrap, FPY, and cycle-time variation
- Use AI and predictive tools for quality detection
- Analyze tool wear and cycle-time anomalies
- Identify scrap patterns and maintenance alerts
- Implement digital tier boards and eAndon systems
- Utilize digital Gemba and IoT data capture
- Maintain the CI pipeline and track financial benefits
- Cascade KPIs across all manufacturing areas
- Execute structured daily and weekly performance reviews
- Train teams on Lean and MAFACT principles
- Coach staff on data-driven decision making
- Promote idea systems and best-practice sharing
- Drive collaborative improvement between component and JIT operations
Berufserfahrung
- 3 - 5 Jahre
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Power BI
- SQL
- DAX
- MES
- Python
- R
Benefits
Startup-Atmosphäre
- Engaging and dynamic environment
Mentale Gesundheitsförderung
- Employee support and resources
Abwechslungsreiche Aufgaben
- Exciting and varied responsibilities
Karriere- und Weiterentwicklung
- Wide range of development prospects
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Magna erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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MAMagna
Group Kaizen Leader(m/w/x)
München
VollzeitVor OrtBerufserfahren
AI/ML
Data Science
Nejo KI-Zusammenfassung
Manual and robotic line rebalancing with SMED and A3 problem solving across seating and component plants. 3-5 years of Lean manufacturing experience in multi-plant operations preferred. Support for multi-site travel, varied process stabilization tasks.
Anforderungen
- Degree in Engineering, Operations, or equivalent experience
- 3–5+ years in Lean/CI manufacturing
- Experience supporting multi-plant operations (advantageous)
- Knowledge of Lean methodologies
- Familiarity with component-plant processes
- Proficiency with Power BI, SQL/DAX, and MES
- Basic analytics, AI, and ML skills
- Clear communication, facilitation, and leadership
- Ability to manage priorities and lead change
- Analytical and structured problem-solving mindset
- Flexibility and willingness to travel
- Lean and Kaizen leadership experience
- Flow optimization and pull systems knowledge
- MAFACT and standardized work deployment skills
- Data analytics, AI/ML, and BI tools proficiency
- Welding, stamping, CNC, and foam process familiarity
- Change leadership and coaching skills
Aufgaben
- Lead CI and Kaizen activities across seating and component plants
- Conduct time studies for manual and automated processes
- Rebalance work content for robotic and manual lines
- Facilitate A3 problem solving and root cause analysis
- Perform 5-Why, SMED, and process stabilization activities
- Implement pull systems and Heijunka principles
- Apply flow principles in assembly and component manufacturing
- Optimize production cells and welding lines
- Improve stamping presses and CNC machining centers
- Optimize foam molding and sub-assembly stations
- Reduce changeover times through SMED
- Ensure tool and mold readiness
- Improve material presentation for high-mix environments
- Develop VSMs for upstream and downstream operations
- Create integrated flow maps for JIT seating
- Deploy Standardized Work and visual controls
- Implement TPM, LPA, and stability-building activities
- Support MAFACT audits and global manufacturing standards
- Build Power BI dashboards to track performance
- Monitor OEE, scrap, FPY, and cycle-time variation
- Use AI and predictive tools for quality detection
- Analyze tool wear and cycle-time anomalies
- Identify scrap patterns and maintenance alerts
- Implement digital tier boards and eAndon systems
- Utilize digital Gemba and IoT data capture
- Maintain the CI pipeline and track financial benefits
- Cascade KPIs across all manufacturing areas
- Execute structured daily and weekly performance reviews
- Train teams on Lean and MAFACT principles
- Coach staff on data-driven decision making
- Promote idea systems and best-practice sharing
- Drive collaborative improvement between component and JIT operations
Berufserfahrung
- 3 - 5 Jahre
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Power BI
- SQL
- DAX
- MES
- Python
- R
Benefits
Startup-Atmosphäre
- Engaging and dynamic environment
Mentale Gesundheitsförderung
- Employee support and resources
Abwechslungsreiche Aufgaben
- Exciting and varied responsibilities
Karriere- und Weiterentwicklung
- Wide range of development prospects
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Magna erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Magna
Branche
Automotive
Beschreibung
Das Unternehmen ist ein Engineering- und Fertigungspartner, der hochqualitative Tanksystemlösungen für PKW und Nutzfahrzeuge anbietet.
Noch nicht perfekt?
- TechBiz Global GmbH
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Vollzeitnur vor OrtSeniorMünchen - ATS Automation Tooling Systems Inc.
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Vollzeitnur vor OrtSeniorHeimstetten - 0066 ICT GmbH
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Vollzeitnur vor OrtBerufserfahrenHeimstetten