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The Data Product Owner (RDQR) leads the strategy, design, and delivery of trusted, high-value data products across McCormick’s combined Research & Development (R&D) and Quality & Regulatory (Q&R) function. This role is accountable for the end-to-end lifecycle, quality, and adoption of RDQR data products that enable measurable business outcomes — including accelerated innovation, improved product quality, and enhanced regulatory compliance.
As a member of the RDQR Transformation Team, the Data Product Owner (RDQR) 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 RDQR data foundation that supports McCormick’s global growth and product innovation strategy.
Key Responsibilities
- Data Product Strategy & Vision: Defines the strategy and roadmap for RDQR 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 RDQR 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 RDQR 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 RDQR 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 RDQR 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 McCormick’s digital and AI transformation
Required Qualifications
- Bachelor’s degree in Data Science, Computer Science, Information Systems, Engineering, Business Analytics, or other applicable field
- Candidates with strong Research & Development (R&D) or Quality & Regulatory (Q&R) academic qualifications and a demonstrated track record of data literacy may also be considered in lieu of the above degree requirements
- 10-12 years of experience in data product management, data strategy, or data governance within a complex or global organization
- 5+ years of experience in R&D and/or Quality & Regulatory 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 end‑to‑end 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 AI‑readiness.
Preferred Qualifications
- Certified Scrum Product Owner (CSPO), Professional Scrum Product Owner (PSPO), or equivalent Agile Product Ownership certification
- Data Management or Analytics-related certifications such as DAMA Certified Data Management Professional (CDMP), Microsoft Certified: Data Analyst Associate
- Familiarity with data cataloging, lineage, or metadata management tools
- Exposure to AI/ML enablement, data democratization, or self-service analytics initiatives
- Demonstrated success in driving cultural transformation toward data-driven decision-making and embedding data governance principles within business processes
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