Head of Enterprise Data & Intelligence

NMDP•Minneapolis, MN

About The Position

The Head of Enterprise Data and Intelligence is an enterprise leader responsible for driving NMDP’s data platform and intelligence strategy, leading a multi-year transformation to a modern, scalable, and AI-ready data ecosystem. Operating at the enterprise level, this role shapes and influences strategy and execution across NMDP enterprises. The Head of Enterprise Data & Intelligence is accountable for building a high-performing organization, establishing a trusted and governed data foundation, and enabling data and intelligence capabilities that directly drive business outcomes and mission impact. This leader serves as a trusted advisor to executive stakeholders, bringing strong executive presence and the ability to influence complex decisions, align cross-functional priorities, and mobilizing teams to deliver measurable value. Success is defined by enterprise adoption, business impact, data trust, and the ability to lead sustained transformation at scale.

Requirements

Knowledge of Enterprise data platforms, modern data architectures, and analytics ecosystems.
Data governance, stewardship, and enterprise data management practices
Regulatory and compliance considerations in complex, regulated environments (e.g., healthcare, life sciences)
Operating models for delivering shared, enterprise-scale data and analytics capabilities
Fiscal management, vendor strategy, and platform cost optimization
Responsible and ethical use of data and AI, including privacy and security principles
Ability to Lead enterprise-wide data and intelligence transformation initiatives from strategy through execution.
Build, develop, and retain high-performing teams and leaders.
Influence and align between senior executives and diverse stakeholders on complex topics.
Communicate with clarity, confidence, and executive presence, including strong presentation skills at all levels.
Translate strategy into practical roadmaps, operating models, and measurable outcomes.
Navigate ambiguity and drive decisive action in complex environments.
Balance strategic thinking with operational execution.
Demonstrate enterprise adoption and satisfaction with data platforms and products.
Measure business value delivered through analytics and AI use cases.
Improve data quality, trust, and accessibility across domains.
Reduce time-to-insight and manual data dependencies.
Demonstrate strong stakeholder alignment and executive confidence in data capabilities.
Bachelor’s degree in computer science, MIS, Engineering, or a related technical field; equivalent experience may be considered in lieu of a degree.
10 or more years of progressive experience in data, analytics, platform, or technology leadership roles leading enterprise scale data platforms or analytics initiatives.
8 or more years of demonstrated experience in people leadership leading teams.
Experience operating in complex, regulated organizations

Nice To Haves

Experience leading AI enabled transformation or advanced analytics initiatives.
Experience in healthcare, life sciences, or other highly regulated environments.
Advanced degree in a related field

Responsibilities

Drive the enterprise vision, strategy, and roadmap for NMDP’s data platforms, analytics, and intelligence capabilities.
Lead the end-to-end transformation from fragmented and legacy data environments to a modern, AI-native, product-oriented data ecosystem.
Establish and mature teams to support a data-as-a-product operating model, including ownership, service accountability, and lifecycle management.
Ensure platforms and data products are scalable, reliable, secure, and aligned to evolving business and research needs.
Serve as a strategic partner to executive leadership, translating enterprise priorities into actionable data and analytics strategies.
Drive alignment across business, research, product, and technology teams to ensure data capabilities enable decision-making, product execution, and measurable outcomes.
Define, track, and communicate clear value metrics, including adoption, data quality, time-to-insight, operational efficiency, and ROI.
Actively socialize, influence, and secure buy-in for complex data and AI initiatives across all levels of the organization.
Provide enterprise-level architectural leadership for data platforms, analytics, and AI-enabled capabilities.
Guide and influence design decisions to ensure alignment with enterprise architecture standards and long-term strategy.
Balance innovation with cost efficiency, scalability, security, and speed to value.
Partner with Enterprise Architecture and AI leadership to ensure a cohesive and future-ready technology ecosystem.
Champion a culture of data trust, accountability, and responsible use across the enterprise.
Establish and operationalize data governance frameworks, stewardship models, and standards aligned to enterprise strategy.
Ensure robust controls for data quality, lineage, metadata, privacy, and access management.
Partner with compliance and security teams to ensure adherence to HIPAA and regulatory requirements, while enabling innovation.
Lead with strong executive presence, serving as a trusted advisor to senior leadership and influencing enterprise decisions.
Build and sustain credible, high-impact relationships across business, research, product, operations, and technology functions.
Drive enterprise alignment and execution in complex, ambiguous, and rapidly evolving environments.
Present strategy, progress, and outcomes to executive and board-level stakeholders, as needed.
Serve as an escalation point for critical platforms, data, and intelligence issues.
Provide strategic oversight of vendor partnerships supporting data and analytics platforms.
Influence and guide technology and tooling decisions in alignment with enterprise priorities and long-term strategy.
Accountable for planning and managing data platform investments and budgets, ensuring cost optimization and measurable ROI.
Ensure vendor performance delivers scalable, high-quality, and value-driven outcomes.
Accountable for enterprise data platform standards, architecture direction, and operating model decisions.
Influences enterprise investment priorities for data, analytics, and AI capabilities.
Shares accountability with business and product leaders for value realization and outcomes of delivery.
Build, lead, and inspire high-performing, diverse teams across data platforms, analytics, and governance.
Establish a culture of accountability, innovation, ownership, and continuous improvement.
Develop leadership capability and succession pipelines within the organization.
Attract and retain top talent to support enterprise transformation and growth.
Build an organization recognized for excellence in data, analytics, and AI within healthcare and research domains.