Onsite Logistics Data & Process Analyst

GMPPU; Concord (NC); Hybrid; USD 80,000 - 110,000; Full time

Benefits offered by this job

401(k) plan

Employer-paid life insurance

32 days annual leave

Employee Assistance Programs (EAP)

Subsidized on-site dining

On-site gym

GM vehicle purchase/lease program

Free on-site EV charging

Job summary

GM Performance Power Units (GMPPU) is seeking a Logistics Process & Data Analyst to join the Warehouse and Logistics Team onsite in Concord, NC. The role focuses on analyzing, improving, and supporting logistics processes through data-driven insights, system optimization, and continuous improvement initiatives.

The ideal candidate will work with multiple teams to drive efficiency, reduce costs, and provide actionable data insights across the end-to-end logistics network, including inventory

Qualifications

• 3+ years in logistics, transportation, or supply chain analytics.
• Experience with TMS, ERP, and reporting platforms.
• Able to work with large datasets and cross-functional stakeholders.
• Strong MS Excel, Power BI, SQL, and data visualization skills.
• Attention to detail and documentation discipline.

Responsibilities

• Analyze warehouse, inventory control, and logistics processes to identify inefficiencies.
• Lead continuous improvement initiatives for transportation, warehousing, and inventory movement.
• Document SOPs and system requirements; map physical to system workflows.
• Develop dashboards and KPIs; provide actionable recommendations.
• Partner with cross-functional teams to improve end-to-end supply chain performance.

Skills

Advanced Excel

Power BI

SQL

Data visualization

Dashboard development

Education

Bachelor's degree in Supply Chain, Logistics, or related field

Tools

TMS

ERP systems

Excel

Power BI

Job description

GM Performance Power Units (GMPPU) is seeking a Logistics Process & Data Analyst to join the Warehouse and Logistics Team onsite in Concord, NC. The role focuses on analyzing, improving, and supporting logistics processes through data-driven insights, system optimization, and continuous improvement initiatives.

The ideal candidate will work with multiple teams to drive efficiency, reduce costs, and provide actionable data insights across the end-to-end logistics network, including inventory