Master Data Analyst (12-month contract)

About the role

Champion Petfoods is expanding! We are excited to announce we are looking for a Master Data Analyst (12-month contract) to join our rapidly growing company. Champion Petfoods is an award-winning pet food maker with a reputation of trust spanning 35+ years. Founded in a small town in Alberta, Canada, Champion – with its ORIJEN® and ACANA® brands – is a key player in the global premium pet food industry across three major geographic regions. We would love to hear from you if you are passionate about personal and professional growth and see yourself as a key player contributing to our continued success as an award-winning company.

Here's The Scoop – Summary We are seeking a detail-oriented and collaborative Master Data Analyst (12-month contract) to join our Project Management Office (PMO). In a fast-paced Consumer Packaged Goods (CPG) environment, clean, consistent, and structured data is the foundation of efficient operations, accurate reporting, and successful new product launches. Reporting directly to the PMO Director and working in close partnership with the Master Data Manager, this "hands-on" role will be responsible for the accuracy, quality, and lifecycle management of our critical business data domains. You will act as the bridge between strategic project milestones (such as New Product Introductions) and the technical execution of Master Data Management (MDM), ensuring that Champion operates with one source of truth. The Master Data Analyst (12-month contract) works out of our Corporate office in Louisville (CO), Nashville (TN) or Edmonton (AB) and works a hybrid schedule with 3 days in-person.

Responsibilities

• Master Data Maintenance & Quality Assurance
  • Data Creation & Management: Execute the hands-on creation, maintenance, and modification of master data records across key domains, with a primary focus on the Product domain (product catalogs, packaging specs, formulation recipes, and hierarchies) as well as Customer, Supplier/Vendor, and Location domains.
  • Data Discrepancy Resolution: Actively troubleshoot data entry errors and resolve naming inconsistencies (e.g., standardizing brand nomenclature like "Six Fish" vs. "6 Fish", "Recipe" vs. "RCP") to prevent downstream operational issues.
  • Auditing & Cleansing: Perform regular data audits and execute cleansing procedures for obsolete, duplicate, or unused data to maintain a clean database and prevent team members from losing valuable time "hunting" for the right information.
  • Standard Operating Procedures (SOPs): Ensure all data-entry activities strictly adhere to established data standards, workflows, controls