Head of Merchandising Data Quality & Taxonomy

Advance Auto Business Support (300); Raleigh (NC); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Health & wellness benefits

Job summary

Advance Auto Parts, Inc. is seeking a Manager of Merchandising Taxonomy & Attribution to oversee enterprise SKU and vendor data integrity, policy enforcement, and data governance across channels.

You will lead a dual-team of policy leads and audit specialists to drive accurate product hierarchies and asset associations. The role requires strong data governance experience in retail, ability to supervise complex audits, and collaboration with cross-functional teams to improve downstream data

Qualifications

• 5+ years in Data Governance, MDM, or Taxonomy Management.
• Experience enforcing data policies in high-volume retail environments.
• Ability to lead a team of policy-driven domain leads and detail-oriented audit specialists.

Responsibilities

• Lead a dual-function team of Domain Governance Leads and Data Audit Specialists to maintain data integrity.
• Enforce clear data governance policies for SKU and vendor data.
• Oversee audits to validate product attributes and digital asset associations.

Skills

Data governance

Team leadership

Data audit

Policy enforcement

Product taxonomy management

Education

Bachelor’s degree in Data Science, Information Management, Business Administration, or related field

5+ years in Data Governance, MDM, or Taxonomy Management

Tools

PIM

DAM

Data governance platforms

Job description

Advance Auto Parts, Inc. is seeking a Manager of Merchandising Taxonomy & Attribution to oversee enterprise SKU and vendor data integrity, policy enforcement, and data governance across channels.

You will lead a dual-team of policy leads and audit specialists to drive accurate product hierarchies and asset associations. The role requires strong data governance experience in retail, ability to supervise complex audits, and collaboration with cross-functional teams to improve downstream data