As part of the Data Management team, the Catalog Data Specialist owns the accuracy, completeness, and on-time delivery of aftermarket catalog and product information across internal systems and external customer channels. This role ensures high-quality catalog releases (applications/fitment and product attributes), performs structured quality checks, improves tools and processes to increase speed-to-market, and provides benchmarking and coverage insights that support Category Management decisions in an international environment. 

• Own regular catalog release cycles and ensure delivery to schedule across defined formats and channels, including internal outputs, customer-specific feeds, and industry-standard exports. 
• Execute structured QA checks pre- and post-release to ensure compliance with internal and external data guidelines. 
• Manage catalog update communications, including what changed, business impact, and timing, to product management and commercial stakeholders. 
• Monitor and improve product and application data quality through routine audits, exception reporting, and coordination of corrective actions with responsible teams. 
• Maintain integrity of product attributes, taxonomy alignment, and digital assets (such as images and content) across systems and channels. 
• Perform competitive catalog benchmarking and calculate range coverage metrics to identify gaps and growth opportunities. 
• Provide actionable insights to Category Management to improve product range attractiveness and prioritization of new applications and product introductions. 
• Continuously improve tools, queries, and workflows to increase efficiency and reduce lead time. 
• Support implementation and adoption of new data tools and enhancements to the Product Information Management (PIM) system, including documentation and user training. 
• Leverage emerging technologies, including AI tools, to improve data quality and speed-to-market. 
• Manage integration of internal research data with third-party and vendor data, ensuring mapping consistency, traceability, and overall data quality. 
• Coordinate cross-system data considerations where product information flows between PIM and ERP systems such as SAP. 
• Apply knowledge of vehicles and vehicle systems to validate fit, form, and function of products. 
• Identify data gaps and errors beyond missing fields by understanding application logic and product life cycles.