RDQR Data Product Manager (HYBRID)

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.
• 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, and Data Stewards to deliver high-quality, secure, and accessible data solutions.
• Oversees release planning and approval in alignment with governance and quality standards.
• Drives adherence to enterprise and functional standards for data quality, lineage, metadata, and compliance across RDQR data products.
• Promotes engagement with data products and activates a culture where data is valued, trusted, and responsibly used as “ground truth”.
• 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.

Required Qualifications

• Bachelor’s degree in Data Science, Computer Science, Information Systems, Engineering, Business Analytics, or other applicable field.
• 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).
• Proven 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.
• Demonstrated success in translating complex data concepts into actionable business insights.
• 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.
• 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.