Supply Chain Master Data Analyst

Hi, Good day! We are seeking a highly analytical Supply Chain Master Data Analyst to drive data governance, system optimization, and operational data integrity across enterprise supply chain functions. This role is ideal for someone who understands how clean, scalable master data directly impacts inventory accuracy, planning, fulfillment, reporting, and enterprise decision-making. You’ll play a critical role in improving data quality, optimizing workflows, and strengthening governance across product and customer master data domains. This is a high-visibility role where you’ll help shape how data is governed, maintained, and leveraged across the organization. You’ll work closely with cross-functional teams to improve operational efficiency, strengthen system reliability, and support scalable business growth. Client: Galderma Job Title: Supply Chain Master Data Analyst (Data Governance & Systems Optimization) Duration: 6 Months Contract (Possible Extension) Work Authorization: W2 (USC and/or Green Card only) Location: 14600 Heritage Pkwy, Fort Worth, TX 76177 (Hybrid – 3 days onsite / 2 days remote) (The client is specifically looking for someone local to Fort Worth, TX and is not open to candidates requiring relocation.) Responsibilities: • Own and maintain master data governance processes across product, customer, and supply chain domains • Develop and enforce data standards, policies, SOPs, and governance controls to ensure consistency and accuracy • Manage item master and product lifecycle data, including finished goods specifications and related attributes • Partner with Supply Chain, Operations, IT, and business stakeholders to resolve complex data issues and improve system integrations • Lead data quality initiatives including cleansing, validation, auditing, and KPI reporting • Perform root cause analysis on data discrepancies and drive long-term process improvements • Support ERP enhancements, testing, migrations, and large-scale data updates • Monitor data flow across enterprise systems and identify opportunities for automation and optimization • Promote data governance best practices through stakeholder collaboration and user training