Data-Driven Lean Six Sigma Process Engineer

Aegis Worldwide; Indianapolis (IN); On-site; USD 80,000 - 110,000; Full time

Benefits offered by this job

401(k) plan

Pension plan

Job summary

A well-established manufacturing organization seeks a Continuous Improvement Process Engineer to lead plant-floor projects focused on process consistency, productivity, quality, waste reduction, and cost savings. The role emphasizes data-driven root-cause analysis and measurable improvements.

The candidate will work with Production, Quality, Engineering, and Maintenance to map processes, conduct structured experiments, and sustain gains across lines.

Qualifications

• Bachelor's degree in Engineering, Operations, Quality, or related technical field.
• 5+ years of manufacturing process improvement experience.
• Hands-on experience with DOE, MSA/Gauge R&R, and Value Stream Mapping.

Responsibilities

• Analyze manufacturing processes for inefficiencies, variation, bottlenecks, and waste.
• Lead process-improvement projects from problem identification through implementation.
• Use data and statistical methods to identify root causes.
• Improve cycle time, throughput, quality, yield, scrap, and overall equipment performance.
• Apply Lean and Six Sigma methodologies.
• Conduct process mapping and structured experiments.
• Evaluate how equipment settings and process inputs affect final product results.
• Develop corrective actions and standardized processes.
• Partner with Production, Quality, Engineering, and Maintenance.
• Track project performance and ensure improvements are sustained.

Skills

DOE

MSA/Gauge R&R

Value Stream Mapping

Data analysis

Lean Six Sigma

Education

Bachelor's degree in Engineering, Operations, Quality, or related technical field

Tools

Statistical software

Process mapping tools

Job description

A well-established manufacturing organization seeks a Continuous Improvement Process Engineer to lead plant-floor projects focused on process consistency, productivity, quality, waste reduction, and cost savings. The role emphasizes data-driven root-cause analysis and measurable improvements.

The candidate will work with Production, Quality, Engineering, and Maintenance to map processes, conduct structured experiments, and sustain gains across lines.