Six Sigma Engineer

EDAG Mexico•Novi, MI

About The Position

The Six Sigma Black Belt Engineer leads data-driven process improvement initiatives across the organization to improve quality, reduce variation, eliminate waste, and drive measurable business results. This role applies advanced statistical methods and Lean Six Sigma methodologies to complex problems, mentors Green Belts and project teams, and partners with leadership to deliver sustainable operational excellence. Lead and execute high-impact Lean Six Sigma projects using DMAIC, DMADV, and Lean methodologies to improve quality, cost, delivery, safety, and customer satisfaction. Serve as a subject matter expert in statistical analysis, variation reduction, process capability, and root cause analysis. Identify improvement opportunities aligned with strategic business goals and quantify financial and operational benefits. Facilitate cross-functional teams through structured problem-solving, change management, and continuous improvement initiatives. Develop project charters, business cases, timelines, and measurable success metrics; track and report project progress and results to leadership. Apply advanced analytical tools, including hypothesis testing, regression, design of experiments (DOE), control charts, and risk analysis. Implement and sustain standard work, control plans, and performance dashboards to ensure long-term results. Mentor and coach Green Belts, Yellow Belts, and project team members in Six Sigma and Lean principles. Support development and evolution of organizational continuous improvement standards, tools, and best practices. Collaborate with engineering, operations, quality, supply chain, and leadership teams to integrate process improvements into daily operations. Promote a culture of data-driven decision making and continuous improvement across the organization.

Requirements

Project Duration: Until 12/31/2030
Bachelor’s degree in engineering, Manufacturing, Operations Management, Industrial Engineering, or a related technical field.
Certified Six Sigma Black Belt (ASQ, IASSC, or equivalent).
Proven experience leading multiple end-to-end Six Sigma or Lean projects with quantified results.
Strong expertise in statistical analysis and problem-solving tools.
Demonstrated ability to influence without authority and lead cross-functional teams.
Excellent communication, facilitation, and presentation skills.
Proficiency with data analysis tools (e.g., Minitab, JMP, Excel, or equivalent).

Nice To Haves

Master’s degree in Engineering, Business, or a related field.
Experience in manufacturing, automotive, aerospace, healthcare, logistics, or regulated industries.
Lean certification or strong Lean implementation experience.
Familiarity with change management principles and organizational transformation initiatives.
Experience coaching and certifying Green Belts.

Responsibilities

Lead and execute high-impact Lean Six Sigma projects using DMAIC, DMADV, and Lean methodologies to improve quality, cost, delivery, safety, and customer satisfaction.
Serve as a subject matter expert in statistical analysis, variation reduction, process capability, and root cause analysis.
Identify improvement opportunities aligned with strategic business goals and quantify financial and operational benefits.
Facilitate cross-functional teams through structured problem-solving, change management, and continuous improvement initiatives.
Develop project charters, business cases, timelines, and measurable success metrics; track and report project progress and results to leadership.
Apply advanced analytical tools, including hypothesis testing, regression, design of experiments (DOE), control charts, and risk analysis.
Implement and sustain standard work, control plans, and performance dashboards to ensure long-term results.
Mentor and coach Green Belts, Yellow Belts, and project team members in Six Sigma and Lean principles.
Support development and evolution of organizational continuous improvement standards, tools, and best practices.
Collaborate with engineering, operations, quality, supply chain, and leadership teams to integrate process improvements into daily operations.
Promote a culture of data-driven decision making and continuous improvement across the organization.