Data Product Manager SAP Analytics (HYBRID)

The Data Product Manager (SAP Analytics) leads the strategy design and delivery of trusted high-value data products for McCormicks SAP Analytics. This role is accountable for the end-to-end lifecycle quality and adoption of SAP Analytics data products that enable measurable business outcomes including strategic decision-making performance transparency and operational excellence across McCormick.

The Data Product Manager (SAP Analytics) is accountable for the definition championing and most importantly delivery of trusted high-value data products. The role works as one with McCormicks Transformation & Technology (including Data & Analytics Data Governance Information Security and Technology teams) and Global Business Solutions (including Automation and Data Science & Engineering teams) functions to connect people platforms and processes establishing a trusted intelligent and connected SAP Analytics data foundation that supports McCormicks global growth and enterprise value creation.

Key Responsibilities

• Data Product Strategy & Vision: Defines the strategy and roadmap for SAP Analytics data products that enable functional priorities and deliver measurable business value in alignment with McCormicks enterprise data strategiesboth at the functional level as established by the Data Owner and at the enterprise level as established by the Chief Data & Analytics Officer (CDAO). Partners with stakeholders and Transformation & Technology Business Relationship Managers (BRMs) to prioritize initiatives based on business impact ROI potential and readiness for advanced analytics and AI applications. Directs the design and delivery of data products that generate tangible business outcomes while ensuring scalability interoperability and longterm sustainability. Establishes and maintains strong crossfunctional alignment to effectively prioritize initiatives communicate progress and advance McCormicks datadriven transformation.
• Data Product Lifecycle Ownership: Directs the planning prioritization and delivery of SAP Analytic data products through an agile iterative approach that ensures responsiveness to evolving business needs. Manages the data product backlogtranslating functional requirements into clear actionable user storiesand directs Data Engineers Data Architects (who are part of the AI and analytics product teams) and Data Stewards to deliver high-quality secure and accessible data solutions. Oversees release planning and approval in alignment with governance and quality standards.
• Data Quality Trust & Compliance: Drives adherence to enterprise and functional standards for data quality lineage metadata and compliance across SAP Analytic data products. Partners with key stakeholders to embed governance and regulatory requirements into data product design and delivery. Monitors data quality and trust metrics driving continuous improvement to ensure data products remain reliable reusable and fit for analytical and AI-driven use cases.
• Data Enablement & Workforce Readiness: Enables relevant stakeholders to easily find understand and use trusted data by ensuring data products are well-documented cataloged and supported with clear usage guidance. Partners with key stakeholders to maintain accurate catalog entries metadata and reference materials that promote consistent and compliant data use. Leads initiatives to strengthen engagement with data products and activate a culture where data is valued trusted and responsibly used as ground truth.
• Data Product Performance & Value Realization: Defines and tracks performance metrics to measure the adoption quality and business impact of SAP Analytic data products. Establishes feedback loops that leverage usage insights and stakeholder input to drive continuous improvement and optimization. Partners with the Data Owner to quantify and communicate data product value demonstrating significant advancement McCormicks digital and AI transformation.

Required Qualifications

• Bachelors degree in Data Science Computer Science Information Systems Engineering Business Analytics or other applicable field
• Candidates with strong SAP Analytics qualifications and a demonstrated track record of data literacy may also be considered in lieu of the above degree requirements
• 9-12 years of experience in data product management data strategy or data governance within a complex or global organization
• 5 years of experience in SAP Analytics within the CPG food or manufacturing industries
• Proven ability to manage the end-to-end lifecycle of data products from vision and roadmap through delivery and adoption
• Strong understanding of data architecture quality metadata and governance with the ability to connect technical design to business value and apply modern data product concepts (e.g. data mesh)
• Demonstrated success working in Agile environments collaborating with cross-functional teams including Data Engineering IT and business stakeholders
• Solid business acumen and communication skills with experience quantifying data product value and driving data adoption across functions
• Demonstrates strong data literacy and the ability to translate complex data concepts into actionable business insights.
• Applies endtoend thinking to connect data strategy architecture and governance across functions and platforms.
• Uses analytical and critical thinking to evaluate data product performance and guide continuous improvement.
• Operates with high accountability and ownership ensuring data products deliver measurable business impact.
• Demonstrates agility and adaptability in managing evolving priorities and emerging technologies within a dynamic data ecosystem.
• Champions innovation by identifying opportunities to enhance data accessibility usability and value creation.
• Maintains a strong commitment to data governance embedding responsible and compliant data practices into everyday decisions.
• Collaborates effectively across technical and functional teams fostering trust and alignment to achieve shared outcomes.
• Displays curiosity and learning agility proactively developing expertise in data management analytics and AIreadiness.

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