Data Product Manager - SAP Analytics; HYBRID
Listed on 2026-06-27
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IT/Tech
Data Analyst, Business Systems/ Tech Analyst, Data Engineering, Data Science Manager
HUNT VALLEY, MD, US, 21031
We are looking to hire a Data Product Manager - SAP Analytics immediately in a Hybrid (50/50) capacity at our Global Headquarters in Hunt Valley, Maryland.
What We Bring To The Table- Career growth opportunities
- Flexibility and Support for Diverse Life Stages and Choices
- Wellbeing programs
The Data Product Manager (SAP Analytics) leads the strategy, design, and delivery of trusted, high-value data products for McCormick’s 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 McCormick’s 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 McCormick’s 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 McCormick’s enterprise data strategies—both 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 long-term sustainability. Establishes and maintains strong cross‑functional alignment to effectively prioritize initiatives, communicate progress, and advance McCormick’s data‑driven 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 backlog—translating functional requirements into clear, actionable user stories—and 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…
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