Engineering Operational Excellence Lead

The Engineering Operational Excellence ( OpEx ) Lead drives engineering transformation across global New Product Introduction (NPI) and engineering value streams.

This role focuses on improving speed, quality, and productivity through data-driven and digital solutions.

This position is ideal for a candidate with 5–10 years of experience who is highly analytical, comfortable with data and modern AI tools, and eager to create measurable impact.

The role involves collaboration with global engineering, program management, test labs, and NPI teams while promoting a culture of operational excellence aligned with the Garrett Excellence Model (GEM).

Build and maintain dashboards, KPI trackers, and performance models using Excel, Power BI, or similar tools.

Perform statistical analysis to identify inefficiencies and opportunities for improvement.

Use AI tools to accelerate data analysis and insight generation.

Develop predictive models for engineering cycle time and risk analysis.

Present data insights clearly to stakeholders.

Promote use of AI tools across engineering processes.

Identify and implement automation for repetitive tasks and reporting.

Support integration of digital tools into existing engineering workflows.

Stay updated on emerging AI technologies and recommend applications.

Support transformation of engineering and NPI processes.

Participate in value stream mapping, Kaizen events, and problem-solving activities.

Apply Lean and Six Sigma concepts with support from senior leaders.

Maintain process documentation and governance practices.

Track improvements in engineering productivity, cycle time, and quality.

Support planning cycles such as AOP and forecasting with performance data.

Bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science, Software Engineering, or a related field.

Master’s degree in Data Science, Analytics, Engineering Management, or Industrial Engineering.

Certification or coursework in AI, machine learning, or analytics.

5–10 years of relevant experience.

Strong experience in data analysis and problem-solving.

Hands-on experience with Excel and data visualization tools like Power BI or Tableau.

Exposure to AI tools or automation.

Industry experience in Automotive or Manufacturing is a plus.

Strong data and analytics skills

Experience with AI tools and automation

Statistical and quantitative thinking

Problem-solving mindset

Clear communication and data storytelling

Learning agility and growth mindset

Ability to collaborate with global teams

Lean Six Sigma (Green Belt or higher)

Data Science or AI certifications