Supply Chain Engineer II — Lead Continuous Improvement

NFI

Trenton (NJ)

On-site

USD 85,000 - 115,000

Full time

6 days ago
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Job summary

NFI is seeking a Supply Chain Engineer II to drive engineering analysis and continuous improvement across warehousing, transload, cross-dock, and transportation operations. The role emphasizes data analytics and proactive communication with customers and management.

The candidate should bring 1–3+ years in supply chain engineering, experience with Lean/Six Sigma, and strong programming/database skills to manipulate large data sets. Travel up to 25% is expected.

Qualifications

  • BS or Business degree required; BS Industrial Engineering preferred.
  • 1-3+ years in supply chain engineering design, transportation management, or related areas.
  • Lean Six Sigma project experience.
  • Working knowledge of warehousing and transportation operations.
  • SQL/Database manipulation skills.
  • Willingness to travel up to 25%.

Responsibilities

  • Lead engineering projects and analysis using engineering methods and tools.
  • Identify process gaps and implement improvements.
  • Establish and monitor performance KPIs and data analytics.
  • Drive continuous improvement with operations and customers.
  • Provide engineering design and supply chain strategy recommendations.
  • Collaborate with engineering and operations managers to implement efficient solutions.

Skills

Data manipulation
SQL
Access
Alteryx
Python
R
C++

Education

Bachelor's degree
BS Industrial Engineering preferred

Tools

AutoCAD
WMS
Routing software
Transportation optimization

Job description

NFI is seeking a Supply Chain Engineer II to drive engineering analysis and continuous improvement across warehousing, transload, cross-dock, and transportation operations. The role emphasizes data analytics and proactive communication with customers and management.

The candidate should bring 1–3+ years in supply chain engineering, experience with Lean/Six Sigma, and strong programming/database skills to manipulate large data sets. Travel up to 25% is expected.

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