We fight friction to move the world forward. 20% of all energy consumed is spent overcoming friction. At SKF, were constantly fighting that friction, to reduce energy waste and make the most of the resources we have. Since 1907, weve been making some of the worlds most innovative bearings, seals, and lubrication systems to reduce friction. But we are selling something bigger. Less friction means more energy saved.. By seeking out and reducing friction, were making industry smarter, more competitive, and more energy efficient. And in collaboration with other forward-thinking companies, actually tackling some of the most pressing challenges of our time. Ultimately, helping to build a more sustainable future where we can all do more with less.
Were looking for a detail-driven Automotive Aftermarket Product Data Analyst to manage, enrich, and validate technical product data for our automotive parts catalog. Youll bridge the gap between OE specifications and aftermarket cataloging systems, ensuring high data accuracy, vehicle fitment integrity, and rapid onboarding of new SKUs into our STEP/PIM environment.
Key Responsibilities:
- Catalog Enrichment: Interpret OE drawings, specifications, and supplier data to create complete, structured product listings (Form-Fit-Function validated).
- Data Validation: Apply logical analysis to detect inconsistencies, duplicates, and fitment conflicts across platforms (STEPMaster Data Management Database, TecDoc, Product Information Management (PIM) etc.).
- OE Data Mapping: Research OE references using Electronic Parts Catalogue (EPC) and cross-brand databases; maintain lineage and supersession details.
- Tool Utilization: Operate Excel, Power Query to manage bulk data updates; assist in automation of QA processes.
- System Knowledge: Understand vehicle systems (engine, suspension, electrical, etc.) to ensure proper categorization and attribute mapping.
- Process Documentation: Draft SOPs, enrichment guides, and change requests in alignment with cataloging best practices.
- Audit & Quality Control: Hands-on periodic audits, maintain scorecards, and collaborate with QC teams to improve data quality.
- Collaboration: Liaise with sourcing, tech, customer support, and vendor teams to clarify catalog content and drive continuous improvement.
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