Data Product Manager
$105k - $120kNational Multiple Sclerosis
WHO WE ARE: The National Multiple Sclerosis Society mobilizes people and resources to drive research for a cure and to address the challenges of everyone affected by MS. To fulfill this mission, the Society funds cutting-edge research, drives change through advocacy, facilitates professional education, collaborates with MS organizations around the world, and provides programs and services designed to help people with MS and their families move their lives forward. We partner with volunteers to accomplish our work. Staff members engage volunteers through effective and timely communications, facilitating meaningful opportunities, and continually seeking and providing feedback for reciprocal growth and learning. Job Summary: The Data Product Manager (Business Data Lead) is responsible for developing shared business data models, definitions, and metric frameworks that enable consistent, scalable, and self-service analytics across the organization. This role partners across business, analytics, and technology teams to ensure enterprise data is understandable, aligned, and actionable in support of operational efficiency, fundraising effectiveness, and strategic decision-making. As part of the organization's Unified Data Foundation (UDF) strategy, this role advances a connected enterprise data ecosystem that improves data accessibility, consistency, usability, and AI readiness. By aligning shared business definitions, metrics, and data structures across systems and teams, the role enables trusted, reusable analytics that support faster and more informed decisions. The position leads cross-functional efforts to establish scalable, business-friendly data foundations, strengthening alignment between business and technology teams and supporting long-term analytics enablement. Location Requirements
- Remote - Flexible Location
- Work is primarily performed remotely, however, when possible and necessary, teams meet in person to conduct the business of the organization and build team relationships.
- Ability to travel approximately 20%
- Considerable Paid Time Off Plan
- Paid Holidays
- 401k Retirement Savings Plan with Society match
- Commuter Benefit Plan
- Medical
- Dental
- Vision
- Flex Spending Accounts
- Life Insurance
- Disability Coverage
- Spring Health Membership offering free therapy and professional coaching, as well as additional voluntary benefit offerings.
- Lead the design, development, and evolution of shared business data models, metrics, and reusable reporting structures that support consistent and scalable analytics.
- Translate business processes and requirements into scalable, business-friendly data models, metric definitions, and reporting logic that enable actionable insights and decision-making.
- Define and maintain standardized business definitions, metric logic, and data relationships while identifying and resolving inconsistencies that impact analytics usability, alignment, and reporting accuracy.
- Collaborate with data engineering, architecture, analytics, and product teams to align enterprise data structures with semantic models, ensuring scalability, performance, and usability.
- Drive adoption of shared business data models and reporting structures by improving data accessibility and enabling intuitive, scalable self-service analytics.
- Improve reporting consistency and trust in enterprise data by reducing duplicate or conflicting metric definitions, supporting faster and more confident business decision-making.
- Facilitate cross-functional alignment by bringing together business, analytics, and technology teams to standardize metrics and build shared understanding of enterprise data.
- Provide subject matter expertise and guidance on data modeling, metric design, semantic layer best practices, and data enablement strategies.
- Evaluate and evolve semantic modeling tools, frameworks, and practices to support organizational growth, changing business needs, and emerging analytics capabilities.
- Manage semantic and business-facing data assets as products, including lifecycle ownership, usability, adoption, and continuous alignment with evolving business and analytics needs.
- Lead cross-functional semantic modeling and analytics enablement initiatives, driving alignment, influencing approaches, and guiding teams toward scalable, business-friendly data solutions.
- At this career level, you are leading in this way: by acting as a knowledge leader in semantic modeling and enterprise data design, defining best practices and guiding others in the effective and consistent use of business data.
- Demonstrated experience in data modeling and semantic layer design, including dimensional modeling, business-facing data structures, and enterprise reporting solutions.
- Experience developing and managing business metrics, definitions, and metric frameworks across multiple functional areas to support consistent analytics and reporting.
- Proven ability to translate business processes and requirements into scalable data models and actionable insights, partnering with stakeholders across business, analytics, and technology teams.
- Understanding of enterprise analytics, business intelligence, and self-service reporting concepts, with experience enabling scalable data access and usability.
- Strong collaboration and facilitation skills, with experience driving cross-functional alignment, standardization, and shared understanding of data and metrics.
- Excellent communication skills, with the ability to clearly explain complex data and technical concepts to non-technical audiences.
- Strong analytical, problem-solving, and organizational skills, with the ability to resolve data inconsistencies and balance strategic design with operational execution.
- Experience supporting adoption of shared business data models, metric frameworks, or enterprise reporting solutions across diverse teams.
- Demonstrated ability to define and scale shared business data models or metric frameworks across multiple teams or functional areas.
- Experience with semantic modeling tools, BI platforms, enterprise reporting tools, or data catalog/search tools
- Familiarity with modern data architectures (e.g., data warehouses, lakehouses, distributed systems)
- Experience contributing to enterprise data standardization or modeling initiatives
- Knowledge of data visualization best practices and analytics user experience design
- Experience driving self-service analytics adoption or business-facing data enablement
- Experience working in product-based, agile, or matrixed organizational environments
- Experience supporting domain-specific data environments such as CRM, revenue operations, fundraising, or similar operational systems
Vacancy posted 1 day ago
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