Data Analyst, Master Data Governance

Why join our team?

• Full benefits package – medical, dental, vision & 401(k) match
• Generous PTO & holidays
• Growth opportunities to expand skillsets & enhance career
• Amazing team & culture focused on: Communication | Community | Wellness

Other Benefits & Programs We Offer:

• Tuition reimbursement
• HSA Medical plan option with annual company contribution
• Referral bonus program
• Perks at Work – discounts on shopping, travel & more
• Proven continued business growth for future opportunities

Position Overview

The Data Analyst, Master Data Governance is responsible for ensuring the accuracy, consistency, and integrity of critical master data within Gehl Food & Beverage’s Ross ERP and related systems. This role manages the setup and maintenance of item, customer, vendor, packaging, GDSN, and pricing data while partnering with cross-functional teams to ensure timely, accurate changes that support order fulfillment, production planning, invoicing, and reporting.

Key Responsibilities

• Item Setup: Create and maintain item master records, including item codes, descriptions, specifications, units of measure, and related attributes. Coordinate with R&D, Sales, Procurement, and Operations to support accurate and timely product launches.
• GDSN Data: Manage product data publication and synchronization through Syndigo/GDSN, ensuring product content meets retailer and distributor requirements. Resolve synchronization errors and retailer rejections.
• Customer & Vendor Data: Create and maintain customer and vendor records, ensuring changes are complete, authorized, accurate, and compliant with internal controls.
• Packaging Data: Maintain case and pallet configurations, unit-of-measure conversions, GTINs/UPCs, and other packaging attributes.
• Pricing: Set up and maintain customer pricing, price lists, promotions, and contract pricing. Validate pricing against approved agreements and resolve discrepancies.
• Data Governance: Follow governance policies, procedures, and approval workflows; identify and resolve data quality issues and duplicate records.
• Continuous Improvement: Recommend process improvements and prepare reporting on data quality, request volumes, and turnaround times.