We, STELLANTIS  Engineering, are seeking a certified  Six Sigma Black Belt  with deep expertise in  Automotive Electrical, Electronics, and Software systems . This role will lead strategic quality and process improvement initiatives across the product development lifecycle—from concept and design to in-field customer quality issues. This position will also be responsible for training, mentoring, and managing skills development across Global cross-functional teams in Engineering and Collaboratively work with Software Engineering (SWE) and Customer Experience Teams

Key Responsibilities:

Lean Six Sigma Leadership:

Lead and execute high-impact Lean Six Sigma projects across product development and quality domains.

Drive root cause analysis and corrective actions for complex design and field issues.

Collaborate with cross-functional teams (Design, Validation, Manufacturing, Quality, and Service) to resolve systemic problems.

Training & Skills Management:

Develop and deliver customized training programs in Six Sigma, problem-solving, and quality tools tailored to Automotive Electrical/Electronics/Software domains with Support and Collaboration from Customer Experience – Proactive Quality Teams.

Assess skill gaps and implement structured development plans for engineers and quality professionals.

Establish and manage certification programs for Green Belts and Black Belts within the organization.

Promote a culture of continuous learning and technical excellence.

Product Development Quality:

Support design teams in applying DFSS (Design for Six Sigma) principles during concept and development phases and other preventive quality tools Reactive Problem solving to mitigate design risks.

Lead cross-functional reviews of field quality issues, warranty data, and customer complaints to identify systemic design or process flaws.

Drive closed-loop corrective actions and lessons learned integration into future programs.

Data Analysis & Reporting:

Utilize statistical tools and software (e.g., Minitab, JMP) and extensive utilization integration of Artificial intelligence to analyze quality data and identify trends.

Develop dashboards and reports to monitor project performance, quality KPIs, and training effectiveness.