Product Data Lead (Hybrid)

Data Acquisition

• Close data gaps across cross-references, fit-up, specs, and model years to support accurate matching
• Research fit-up and cross-reference data so customers and dealers can find compatible products
• Gather key data to link equipment to compatible replacement products
• Lead data collection through research, partner networks, and cross-functional collaboration
• Manage contractors, crowd-sourced input, and approved third-party sources
• Standardize collection formats and validate data before handoff

Data Integrity

• Partner with Marketing UI and IT to support Part Finder and data standards
• Document new data relationships and communicate updates internally
• Validate fit-up and cross-reference data for accuracy and completeness
• Work with the Data Analyst to prepare data for Hybris and resolve issues
• Audit Oregon Tool and third-party sites and report trends to product managers

Continuous Improvement

• Support Part Finder launches by preparing, exporting, and testing data
• Identify top cross-reference sources to improve fit-up data coverage
• Use stakeholder and end-user insights to improve data quality and experience
• Improve data sourcing, processing, and scraping, including AI tools

Qualifications & Skills

• Bachelor’s Degree with an emphasis in Data Analytics, Marketing, Business Administration, Information Systems, or related discipline preferred, or equivalent professional experience
• Minimum of 3 to 5 years of experience in a data-focused, product data, or data sourcing role, or equivalent combination of education and experience
• Demonstrated experience working with large, complex, and often unstructured data sets with strong attention to detail
• Data acquisition, data validation, and data organization experience across multiple internal and external sources
• Experience working in a global environment with cross-functional teams and geographically dispersed data sources
• Experience coordinating and managing projects involving multiple inputs, contributors, and dependencies
• Familiarity with data sourcing, web research, and data extraction techniques; web scraping experience a plus
• Strong written and verbal communication skills; able to clearly express information in both technical and non-technical terms
• Proficiency in Microsoft Office Suite (Outlook, Word, Excel, PowerPoint), with emphasis on intermediate to advanced Excel skills for data mapping, comparison, and analysis
• Comfortable leveraging modern productivity and AI-enabled tools to improve efficiency and data processes