The Data Product Manager is responsible for leading the lifecycle of data-centric products, with a strong emphasis on 0-to-1 product ideation, prototyping, and execution — translating ambiguous opportunities into validated, scalable data products aligned with user needs and business value within the Data Office.
Key Responsibilities
Product Strategy and Vision
Define data product strategy and vision aligned with NEE and Data Office goals.
Develop a product roadmap that evolves with changing user needs, including phased 0-1 to scaled delivery planning.
Identify Enterprise Data opportunities and user needs through research, analysis, and emerging technology assessment.
Product Discovery & 0-1 Ideation
Lead 0-to-1 product ideation cycles, transforming undefined problem spaces into structured product concepts with clear business cases.
Conduct design sessions with business unit stakeholders to ideate and yield draft product requirements.
Conduct user interviews and surveys to gather insights and validate product concepts.
Develop mockups, wireframes, and low-fidelity prototypes to rapidly test and validate hypotheses prior to full development.
Conduct usability testing on prototypes and iterate based on stakeholder and end-user feedback.
Engage in competitive analysis to identify differentiation opportunities.
Utilize data-driven techniques to uncover emerging trends and inform discovery.
Prototyping & AI Development
Architect and deliver functional 0-1 prototypes, including AI-enabled capabilities, to demonstrate product value and de-risk full-scale investment.
Lead the design and development of AI agents within prototype environments, defining agent objectives, tool integrations, orchestration logic, and evaluation criteria.
Collaborate with data scientists and engineers to incorporate generative AI, ML models, or LLM-based components into prototypes as needed to meet product goals.
Establish prototype success criteria and manage the transition from prototype to production-ready product.
Product Development & Tech Oversight
Partner with engineering, solution architects, and business unit stakeholders to translate discovery insights and validated prototypes into product features.
Oversee the use of data migration development tools (e.g., Databricks, AWS Glue, DMS, or equivalent) to support data movement, transformation, and pipeline development within the product lifecycle.
Prioritize features and functionalities based on business impact and technical feasibility.
Stakeholder Management
Engage with stakeholders across the organization to gather requirements and communicate product status.
Advocate for product within the company and ensure alignment with business objectives.
Provide training and support for users and stakeholders to maximize product adoption.
Data Analysis and Insights
Utilize data analysis tools to derive insights and inform product decisions.
Ensure the accuracy and quality of data within products.
Performance Metrics and Reporting
Define and monitor KPIs to assess product performance and return on investment (e.g., product-level Profit and Loss forecasting and analysis).
Manage budget for product development and ensure optimal resource allocation.
Prepare reports and presentations to communicate results and insights.
Create product collateral (e.g., Product Charters, prototype summaries, case studies, 1-pagers).
Qualifications
Bachelor's degree in Computer Science, Engineering, Data Science, or related analytical field.
Master's degree in an analytical field preferred.
Experience in product management with a focus on data products, discovery, and 0-to-1 product delivery.
Strong technical background with an understanding of data technologies, AI/ML tooling, and data migration frameworks.
Excellent communication skills and ability to work cross-functionally.