Head of Enterprise Data & AI Platform Architecture

Relha LLC

Durham, Northern (NC, KY)

Hybrid

USD 120,000 - 334,000

Full time

15 hours ago

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Job summary

IQVIA seeks a strategic, hands-on Director of Enterprise Data & Digital Platform Architecture to define and lead the architecture vision for next‑generation data, analytics, and AI platforms in healthcare and life sciences. You will drive scalable, cloud-native, compliant platforms and reusable capabilities across product and engineering teams.

You will partner with product, data, business, and compliance stakeholders to set standards, guide investments, and advance enterprise-wide digital

Qualifications

Bachelor's degree in computer science, engineering, information systems, or related discipline (Master's preferred).
12+ years of experience in architecture, engineering leadership, or enterprise technology roles, including leadership of large-scale platform or digital transformation initiatives.
Proven experience designing and governing enterprise-scale cloud and data architectures.
Deep expertise in cloud platforms like AWS, Azure, Snowflake, Databricks, Kubernetes, API-first architectures, event-driven platforms, and modern integration patterns.
Strong knowledge of data management disciplines including data governance, metadata management, master data management, semantic models, and data products.
Experience architecting AI/ML, advanced analytics, or intelligent automation solutions in regulated environments.
Strong understanding of life sciences, healthcare, or other regulated industries, including standards such as HIPAA, GxP, 21 CFR Part 11, FHIR, HL7, and CDISC.
Demonstrated success leading enterprise modernization, cloud migration, or platform transformation programs.
Excellent communication, executive presence, and stakeholder management skills.
Ability to influence strategic decisions and drive alignment across business, product, engineering, and technology organizations.

Responsibilities

Architecture Strategy & Technology Roadmap: Develop and maintain the long-term architecture vision, reference architectures, and technology roadmaps that support data, analytics, AI, and digital platform initiatives across the organization.
Enterprise Data Architecture: Define scalable data architecture patterns including data products, master data management, metadata management, semantic layers, ontology frameworks, and governed data foundations that enable enterprise-wide data reuse and interoperability.
AI & Intelligent Platform Enablement: Establish architectural patterns that support AI/ML, generative AI, agentic workflows, knowledge services, and advanced analytics while ensuring governance, traceability, and regulatory compliance.
Platform Modernization: Lead modernization efforts utilizing cloud-native technologies, event-driven architectures, microservices, APIs, and modern data platforms such as Azure, Snowflake, Databricks, and emerging cloud services.
Interoperability & Integration: Drive standards-based integration strategies leveraging healthcare and industry standards such as FHIR, HL7, CDISC, APIs, and event-driven frameworks to enable seamless data exchange across internal and external ecosystems.
Design Governance & Architecture Standards: Establish architecture principles, design review processes, technology standards, reusable patterns, and architectural guardrails that promote consistency, security, and scalability across products and platforms.
Strategic Program Leadership: Provide architectural leadership across major transformation programs and strategic investments, ensuring alignment with enterprise priorities and long-term technology strategy.
Emerging Technologies & Innovation: Evaluate emerging technologies and industry trends in AI, data management, digital health, interoperability, cloud computing, and platform engineering; recommend adoption strategies where appropriate.
Organizational Leadership & Mentoring: Mentor architects and senior engineers, fostering a culture of technical excellence, innovation, collaboration, and continuous learning.