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Data & Process Excellence Manager(m/w/x)
Governing quality-relevant data, dashboards, and databases for process automation. Lean Six Sigma Green or Black Belt expertise required. Flexible working hours, comprehensive social benefits.
Requirements
- Bachelor's or Master's degree in Engineering, Business Administration, or comparable discipline
- Excellent analytical and communication skills
- Structured, solution-oriented mindset
- 6–8 years relevant experience in complex, international, or matrix organizations
- Proven expertise in Lean Six Sigma (Green or Black Belt)
- Continuous improvement methodologies expertise
- Certified SCRUM Master
- Experienced in agile delivery
- Crossfunctional collaboration experience
Tasks
- Govern quality-relevant data, dashboards, and databases
- Validate data plausibility
- Drive continuous improvement measures for data quality
- Lead quality-related IT and digitalization initiatives
- Act as SCRUM Product Owner or Project Manager
- Manage initiative scope, backlogs, sprints, risks, governance, and documentation
- Perform advanced data analytics on global quality performance
- Derive actionable insights from data, including OKRs and CX metrics
- Consult, coach, and guide global process managers
- Facilitate process excellence workshops
- Run continuous improvement programs
- Own and maintain Corporate Quality Standards
- Co-lead the Traceability Board
- Support and coach Quality Lean Managers
- Deliver Lean Six Sigma training and workshops globally
Work Experience
- 6 - 8 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Lean Six Sigma
- SCRUM Master
Benefits
Flexible Working
- Flexible working hours
Learning & Development
- Versatile training and further education
- E-learning
Mentorship & Coaching
- Internal knowledge transfer
Other Benefits
- Comprehensive social benefits
Retirement Plans
- Company pension scheme
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Data & Process Excellence Manager(m/w/x)
Governing quality-relevant data, dashboards, and databases for process automation. Lean Six Sigma Green or Black Belt expertise required. Flexible working hours, comprehensive social benefits.
Requirements
- Bachelor's or Master's degree in Engineering, Business Administration, or comparable discipline
- Excellent analytical and communication skills
- Structured, solution-oriented mindset
- 6–8 years relevant experience in complex, international, or matrix organizations
- Proven expertise in Lean Six Sigma (Green or Black Belt)
- Continuous improvement methodologies expertise
- Certified SCRUM Master
- Experienced in agile delivery
- Crossfunctional collaboration experience
Tasks
- Govern quality-relevant data, dashboards, and databases
- Validate data plausibility
- Drive continuous improvement measures for data quality
- Lead quality-related IT and digitalization initiatives
- Act as SCRUM Product Owner or Project Manager
- Manage initiative scope, backlogs, sprints, risks, governance, and documentation
- Perform advanced data analytics on global quality performance
- Derive actionable insights from data, including OKRs and CX metrics
- Consult, coach, and guide global process managers
- Facilitate process excellence workshops
- Run continuous improvement programs
- Own and maintain Corporate Quality Standards
- Co-lead the Traceability Board
- Support and coach Quality Lean Managers
- Deliver Lean Six Sigma training and workshops globally
Work Experience
- 6 - 8 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Lean Six Sigma
- SCRUM Master
Benefits
Flexible Working
- Flexible working hours
Learning & Development
- Versatile training and further education
- E-learning
Mentorship & Coaching
- Internal knowledge transfer
Other Benefits
- Comprehensive social benefits
Retirement Plans
- Company pension scheme
About the Company
Endress+Hauser
Industry
EnergyAutomation
Description
Das Unternehmen entwickelt nachhaltige Produkte für die Durchflussmessung, um Prozesse umweltfreundlicher und effizienter zu gestalten.
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