Data Product Manager

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. Product Development & Tech Oversight Partner with engineering, solution architects, and business unit stakeholders to translate discovery insights and validated prototypes into product features.

Job Title: Data Product Manager
Location: Juno Beach, FL
Duration: 3 Months

Position Overview
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.

EEO:
“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”