Job DescriptionJob Summary: The Data Audit Analyst is a key technical contributor responsible for the rigorous execution of data quality standards across SKU and vendor data domains. In this role you will perform high-volume audits of product attributes, digital assets, and non-application catalog data to ensure accuracy and consistency. This role is critical in ensuring that all item data is validated before downstream syndication, directly impacting the customer experience across retail, professional, and e-commerce channels.
Key Responsibilities: - Data Syndication Validation: Execute comprehensive audit protocols to ensure SKU and category data syndicates accurately to all downstream channels.
- Digital Asset Auditing: Conduct detailed inspections of digital assets, verifying that images, videos, and technical documents are correctly linked to the appropriate SKUs and meet enterprise quality standards.
- Non-Application Catalog Management: Maintain and audit non-application catalog data, ensuring that product hierarchies and attributes align with merchandising strategies and organizational standards.
- Defect Identification: Proactively identify systemic data defects and inconsistencies during audit cycles; document root causes and collaborate with appropriate technology teams to implement permanent fixes.
- Vendor Data Compliance: Audit incoming vendor-provided data and assets to ensure strict compliance with internal requirements before they enter the production ecosystem.
- Audit Reporting: Develop and maintain data quality scorecards and audit reports to provide visibility into the health of the enterprise item data domain.
Qualifications: - Demonstrated experience in high-volume data auditing, preferably within a complex retail or e-commerce environment.
- Strong technical understanding of how master data flows through PIM (Product Information Management) and DAM (Digital Asset Management) systems.
- Exceptional attention to detail with the ability to identify subtle data patterns and anomalies.
- Proficiency in managing and auditing complex product hierarchies and merchandising categorizations.
Certifications, Experience, and Education: - Experience: 3+ years in Data Quality, Data Auditing, MDM, or Merchandising Operations; experience in a senior or lead technical role is preferred.
- Education: Bachelor's degree in Information Management, Data Science, Business, or a related field; OR equivalent relevant work experience.
Location & Work Availability: This position is Hybrid (4 days in office, 1 day remote), based at our corporate headquarters in Raleigh, North Carolina.
Benefits Summary: We believe in supporting our Team Members and those they love through comprehensive health & wellness benefits. Learn more here:
Company Overview: Advance Auto Parts, Inc. is a leading automotive aftermarket parts provider that serves both professional installer and do-it-yourself customers. As of January 3, 2026, Advance operated 4,305 stores primarily within the United States, with additional locations in Canada, Puerto Rico and the U.S. Virgin Islands. The Company also served 809 independently owned Carquest branded stores across these locations in addition to Mexico and various Caribbean islands. Additional information about Advance, including employment opportunities, customer services, and online shopping for parts, accessories and other offerings can be found at
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age national origin, religion, sexual orientation, gender identity, status as a veteran and basis of disability or any other federal, state, or local protected class.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age national origin, religion, sexual orientation, gender identity, status as a veteran and basis of disability or any other federal, state or local protected class. We comply with all applicable federal, state, and local laws.
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