Purchasing Supplier Development Buying Associate

Job Title:
Purchasing Supplier Development Buying Associate

Duration : 12 months contract(possibility of extension)

Pay: $28/hour on a w2 basis without benefits/holiday/vacation

Shift Timing: 8 am to 04:30pm

• Execute buying Operating Procedures (OPs) including supplier set up, price variance management, and payment requisitions.
• Process and manage SAP/Ariba PR/PO data
• Weekly report management
• Supplier follow-up to confirm data, request information, and late requests status
• Document & update business process OPs to improve divisional efficiency
• Manage document distribution, organization, and retention
• Resolve day-to-day supplier issues related to system communication failures, payment issues, late assignments, etc.
• Support company events such as North American Supplier Meeting, etc.
• Overall administrative duties (travel, catering, expense reports, meeting scheduling)

This position will be working at the Plano Texas Headquarter site

• Associate degree or higher or 2+ years equivalent experience in a professional business environment
• Minimum 1 year experience working in a direct or support role in Automotive Buying/Purchasing/Procurement
• Proficiency with Microsoft Excel including ability to complete macros, pivot tables and VLOOKUP (candidates must be tested and score 80% or better)
• Proficiency with PowerPoint (intermediate or above...candidates must be tested and score 80% or better)
• Working experience with Microsoft Power BI (including data links, slicer manipulation, report filters and basic troubleshooting)

• Bachelor's Degree or higher
• Minimum 1 year experience working directly in TMNA as a Team Member or Contractor
• Proficiency with Microsoft Power BI (including data importation, report creation and intermediate troubleshooting)
• Minimum 1year experience with Microsoft Visio or Lucid, including flow chart creation and modification
• Minimum 1 year Experience with SAP Ariba
• Experience with gap analysis and problem identification through understanding of large data sets and procedures