Vendor Master Data Analyst — SAP & Ariba Expert

AbbVie

Illinois

On-site

USD 90,000 - 120,000

Full time

14 days+

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Benefits offered by this job

Health insurance
401(k) plan
Paid time off
Short-term incentive program

Job summary

AbbVie in Illinois is seeking a Senior Analyst to govern and maintain Vendor Master data globally. You will collaborate with Procurement, Accounts Payable, and Treasury to ensure authenticated vendors are onboarded and maintained, while aligning with AbbVie data standards and SLAs.

The role requires experience with SAP S/4HANA, Ariba, and DSP, along with strong analytical and Excel skills to support data quality and process improvements.

Qualifications

  • Bachelor’s degree in finance or accounting is required.
  • 6+ years of relevant experience in Finance or Accounting.
  • Strong communication skills and customer support.
  • Proficient Excel skills required.

Responsibilities

  • Govern and maintain Vendor Master data in SAP S/4HANA across global processes.
  • Collaborate with Procurement, Accounts Payable, Treasury and business users to onboard and maintain vendors.
  • Verify onboarding documentation and updates to Vendor Master data.
  • Prepare process documentation and work instructions for improvements to vendor maintenance systems (Ariba, DSP, SAP, Coupa).
  • Address queries from business requestors and respond to escalations.
  • Maintain strict adherence to AbbVie processes and SLAs.

Skills

S4 SAP Vendor Master
Excel
Analytical skills
Communication
Time management

Education

Bachelor's degree in Finance or Accounting

Tools

SAP S/4HANA
SAP Ariba
DSP
Coupa
Excel

Job description

AbbVie in Illinois is seeking a Senior Analyst to govern and maintain Vendor Master data globally. You will collaborate with Procurement, Accounts Payable, and Treasury to ensure authenticated vendors are onboarded and maintained, while aligning with AbbVie data standards and SLAs.

The role requires experience with SAP S/4HANA, Ariba, and DSP, along with strong analytical and Excel skills to support data quality and process improvements.

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