Director, Data & Analytics Product Management

Role summary

Data and analytics product strategy

• Define, communicate, and execute enterprise data and analytics product strategy aligned with organizational priorities, business objectives, and technology strategy.
• Establish product vision and multiyear roadmaps for data, analytics, reporting, AI, and information-sharing products.
• Identify opportunities for new products, analytical services, AI-enabled capabilities, and reusable data assets that increase the value, accessibility, and responsible use of data.
• Translate organizational strategies and complex business challenges into product opportunities, investment recommendations, and actionable delivery plans.
• Develop product business cases covering user needs, expected outcomes, resource requirements, dependencies, risks, and organizational value.

Portfolio leadership and governance

• Lead planning, prioritization, and management of the enterprise data and analytics product portfolio.
• Establish transparent product intake, evaluation, prioritization, and roadmap-planning processes.
• Define portfolio governance, decision rights, product standards, and performance expectations across the product lifecycle.
• Evaluate product performance and portfolio health using objectives, key results, adoption measures, service-level expectations, business outcomes, and return-on-investment indicators.
• Lead quarterly and annual planning, including resource allocation, dependency management, capacity planning, and roadmap adjustments.
• Manage product risks, technical dependencies, data limitations, implementation barriers, and organizational change impacts.
• Establish processes to retire, consolidate, or modernize products that no longer meet business, technical, or user requirements.

Product development and lifecycle

• Oversee products from user research and discovery through design, development, launch, adoption, support, and continuous improvement.
• Lead delivery of scalable data products, curated datasets, analytics applications, dashboards, data pipelines, APIs, decision-support tools, and AI-enabled solutions.
• Ensure teams use user-centered practices, including stakeholder interviews, requirements definition, prototyping, usability testing, and structured feedback.
• Translate business needs into product requirements, user stories, acceptance criteria, roadmaps, and measurable success indicators.
• Establish reusable standards for discovery, documentation, backlog management, release planning, testing, deployment, support, and performance evaluation.
• Partner with data architecture, engineering, analytics, security, and governance teams to ensure products are aligned with organizational and technical needs.

Requirements

• Lead a multidisciplinary team responsible for product management, data product engineering, analytics delivery, and related capabilities.
• Work with executive leaders and stakeholders across business functions, operations, finance, and technology.
• Align data and analytics product investments with organizational strategy, technical architecture, data governance requirements, and measurable business outcomes.
• Serve as a senior advisor on data and analytic product opportunities, analytics capabilities, artificial intelligence, emerging technologies, and data-asset value.
• Represent the data and analytics product function in enterprise planning, vendor engagements, and external partnerships.