Product Manager, Data-Supply Chain

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Duration: 5+ Months

Location: MN
- Maplewood, Hybrid 3-4 days onsite

Overview: Every Turnberry consultant belongs to a practice, an internal group of consultants and leaders with shared experience and expertise. Each of these practices aligns to one of the core services Turnberry offers to clients. As a Product Manager, Data-Supply Chain, you will join Turnberry's Business Transformation practice. Turnberry's Business Transformation practice is dedicated to diagnosing and addressing core business challenges including regulatory compliance, full-scale implementation, managing change and driving continuous improvement across transformation initiatives.

• Strategic Leadership
  • Define the vision and strategic roadmap for manufacturing data products in alignment with enterprise data strategy and platform capabilities
  • Establish consistent standards for product management, backlog prioritization, and value measurement
  • Identify opportunities for technology-driven improvements and innovations within the supply chain
  • Partner with Data Platform and Architecture teams to ensure data products are scalable, secure, and interoperable across domains
  • Translate enterprise priorities into clear, actionable domain product roadmaps that balance innovation, compliance, and technical sustainability
• Portfolio and Delivery Management
  • Oversee the data product portfolio: lifecycle management, investment planning, and roadmap execution
  • Prioritize across domains based on business value, readiness, and capacity – using intake, ITOC, and BRM processes for governance and alignment
  • Ensure product roadmaps integrate with the broader Data Platform 2.0 architecture (Bronze/Silver/Gold, Iceberg/S3, Glue, Lake Formation, Snowflake, Power BI)
  • Track KPIs: adoption rate, data product usage, cost per TB, cycle time, and ROI metrics
  • Drive cross-domain collaboration and dependency management to maximize reuse and avoid duplication of effort
• Governance and Enablement
  • Embed governance and AI risk reviews into product lifecycle
  • Ensure adherence to data quality, metadata, lineage, and Fin Ops standards
  • Partner with the Security and Risk teams to ensure all products meet global regulatory and compliance requirements
  • Advocate for product reusability, domain ownership, and self-service enablement
• Stakeholder Engagement
  • Build strong relationships with Enterprise Supply Chain domain leaders and IT counterparts to align priorities and outcomes
  • Represent the manufacturing data product portfolio at executive steering committees and enterprise planning sessions
  • Communicate the business impact of data investments in measurable terms – connecting analytics outcomes to operational and financial KPIs
  • Serve as an evangelist for data as a product, driving awareness and adoption across the enterprise

• 8–12+ years of experience in data product management, data strategy, or analytics leadership, with a focus on supporting supply chain operations within a global manufacturing or industrial enterprise
• Proven experience leading teams of product owners, analysts, or engineers
• Deep understanding of data product management principles, domain ownership, and data mesh concepts
• Strong grasp of modern cloud data platforms and toolsets (AWS, Snowflake, Databricks, Glue, Lake Formation, Power BI, dbt)
• Familiarity with Fin Ops, AI Risk, and Data Governance frameworks
• Demonstrated ability to translate business strategies into technical data solutions and measurable value delivery
• Skilled communicator able to influence senior business and technical leaders in a matrixed global organization
• Experience in agile methodologies (Scrum, Kanban, SAFE) with hands‑on product delivery oversight
• Strong problem‑solving skills and the ability to think strategically and analytically
• Bachelor's or Master's degree in Supply Chain Management, Engineering, Data Science, Business, or a related field
• Master's degree or MBA is preferred

The salary range for this role is $110,000 to $155,000 or the hourly equivalent. Pay is based on several factors including but not limited to education, work experience,…