Supply Chain Project Manager

We are transforming how data and analytics deliver value across our global manufacturing ecosystem—shifting from siloed projects to domain-owned, product-centric delivery. The Product Manager, Data – Supply Chain will lead the strategy, development, and management of data-driven products that enhance and enable supply chain operations. This leader owns the full product lifecycle—from discovery and roadmap definition through delivery, adoption, and continuous improvement—ensuring each product directly advances outcomes such as productivity, yield, sustainability, and cost efficiency.

This role requires a strategic thinker with a deep understanding of data analytics, data product management, and technology trends. The ideal candidate will act as the strategic bridge between business functions, data platform engineering, and AI enablement, shaping a globally scalable portfolio of data products that adheres to enterprise governance, Fin Ops, and AI risk frameworks.

• 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.

• 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.

• 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.

• 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.

Master's degree in Supply Chain Management, Engineering, Data Science, Business, or a related field. A Master's degree or MBA is preferred.

70-75/HR