Principal, Data Strategy and Architecture

Job Description

The Principal, Data Strategy and Architecture is a senior individual contributor responsible for providing enterprise-level technical, architectural and governance leadership in support of NMDP's approved enterprise data strategy.

This role serves as a technical authority and trusted advisor, guiding target-state data architecture, governance standards, and platform alignment to enable advanced analytics, AI/ML, and integrated data capabilities across clinical, research (CIBMTR), donor, and operational domains.

This leader is expected to operate with strong executive presence, effectively socializing complex technical strategies, influencing decisions, and securing stakeholder buy-in across all levels of the organization.

This individual will influence outcomes through architectural leadership, technical standards, and cross-functional partnership, ensuring that NMDP's multi-year data transformation is scalable, cohesive, and aligned with industry-leading practices.

This role also requires the ability and presence to help enterprise data transformation efforts, shaping both direction and adoption across the organization.

KEY ACCOUNTABILITIES

Enterprise Data Strategy Execution:


* Provide technical leadership to own data strategy and operationalize NMDP's approved enterprise data strategy.


* Translate strategic objectives into target-state architectural principles, standards, and reference designs.


* Ensure alignment across data platforms, data products, and governance frameworks as the organization transitions from current data environments to an AI-native architecture.


* Drive alignment and adoption of the data strategy by effectively communicating vision, value, and tradeoffs to diverse stakeholder groups.

Data Architecture Leadership:


* Serve as the most senior technical authority for enterprise data architecture in partnership with Enterprise Architecture and IT.


* Define and maintain target-state architecture patterns for data platforms, interoperability, metadata, lineage, and master data management.


* Evaluate and guide major technology and architectural decisions to ensure long-term scalability, security, and interoperability.


* Influence the modernization of legacy systems toward a unified, governed, cloud-enabled data ecosystem.

Data Governance & Trust Enablement:


* Provide technical guidance to support data governance models with ownership embedded in enterprise business domains.


* Define architectural and technical standards for data quality, metadata, lineage, access, consent, and privacy.


* Ensure governance approaches support regulatory compliance, donor and patient trust, and responsible use of data and AI/ML.

Analytics, Data & AI/ML Enablement:


* Guide architectural approaches that enable analytics, data engineering, and AI/ML capabilities across domain and product teams.


* Define technical standards and enablement approaches for data product...