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
Description:
Key Responsibilities:
- 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
Qualifications
- 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)
Added Bonus
- 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