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Master Data Analyst

Insight Global•Toronto, Ontario
Full-time1-3
👁️ 0 views•📝 0 applications•Posted 10/22/2026•Expires 11/21/2026
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Job Description

Insight Global is seeking a Master Data Analyst to support a product-focused business team responsible for maintaining high-quality master data across enterprise systems. This individual will serve as a key partner to Brand Managers and cross-functional stakeholders, helping ensure product information is accurately created, validated, and maintained throughout the product lifecycle. The ideal candidate combines strong analytical skills with excellent communication skills and is comfortable working directly with business users to improve data quality and resolve issues. This is not a data entry position. The successful candidate will be responsible for reviewing, validating, analyzing, and improving product master data while helping stakeholders understand and follow established processes and requirements. Roles & Responsibilities - Partner with Brand Managers and business stakeholders to support product master data initiatives - Review, validate, and maintain product, material, SKU, UPC, and related master data - Ensure data accuracy, completeness, and compliance with established business processes - Identify data quality issues and work with stakeholders to resolve discrepancies - Support product setup activities and ensure information is properly structured within business systems - Guide stakeholders through data requirements and provide coaching on best practices when required - Collaborate with cross-functional teams including Supply Chain, Operations, Finance, and Product teams - Analyze data issues, recommend improvements, and help drive process efficiency - Support ongoing ERP and business transformation initiatives as needed Skills and Requirements - 1-3+ years of experience in Master Data, Product Data, Material Data, or related Data Analyst functions - Experience within manufacturing, consumer products, retail, or CPG environments - Strong understanding of product hierarchies, SKU structures, UPCs, and product master data - Experience validating, maintaining, and improving data quality across business systems - Strong analytical and problem-solving skills with the ability to investigate issues and drive resolutions - Excellent communication skills and confidence working directly with business stakeholders - Experience partnering with cross-functional teams to gather requirements and ensure data accuracy - Ability to educate, guide, and challenge stakeholders when required to maintain data quality standards Strong attention to detail, organization, and follow-through - Experience working with SAP - Understanding of SAP Material Master Data concepts - Experience supporting ERP implementations, transformations, or system migrations - Advanced Excel skills for validation, auditing, reconciliation, and data analysis - Power BI, reporting, or analytics experience Experience supporting product launches, product setup, or product lifecycle processes We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to HR@insightglobal.com.

Required Skills

Master DataProduct DataMaterial DataSAPExcelPower BImanufacturingconsumer productsretailCPGdata qualitydata analysisERPdata validationdata maintenanceproduct lifecycleSKUUPCdata discrepanciescross-functional collaborationprocess efficiency

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