Critical to success is deep familiarity with clinical operations and clinical trial management domains, including understanding of study design, site and patient management, regulatory compliance workflows, data integration across clinical and operational systems, and how technology and AI/agent-based capabilities can be applied tooptimizetrial execution andClinical Operationsefficiency.

Preference will be given to candidates with hands-on experience in clinical trial management, site operations, patient cohort management, or related clinical domains, combined with ability to use enterprise architecture tools and capability models as the stable backbone for processes, products, data, and automation across business units.

Job overview

The Principal Enterprise Architect is accountable for co-designing target-state enterprise architectures and reference models with business, technology, and product leaders, and for prescribing standards, patterns, and guardrails that ensure consistency and scalability across IQVIA. The roleprovidesa portfolio-wide view of business and technical capabilities, surfacing cross-cutting needs and opportunities toconsolidateplatforms and services in both application and data domains. Within clinical operations and clinical trial management, the architect willestablishpatterns and standards that govern how data flows across trial planning, site activation, patient recruitment, data collection, and trial closeout workflows, ensuring that technology investments support operational excellence and regulatory compliance.

Key responsibilities

• Co-design andmaintainenterprise architecture principles, standards, and reference architectures in partnership with business, technology, and product leaders, with explicit focus on clinical operations and clinical trial management to ensure that architecture patterns reflect the realities of study execution, site management, regulatory compliance, and patient safety.

• Define target enterprise data, AI, and interoperability reference architectures, including standard patterns forevent driven architectures(e.g., Kafka), API management (e.g., Apigee, Azure API Management, Kong), and AI/ML platforms (e.g., Azure ML, SageMaker), and ensure initiatives align to these standards and roadmaps. Within clinical domains,establishpatterns for EDC integration, clinical data warehousing, site and patient data orchestration, and agentic AI for trial feasibility, site matching, and cohort discovery.

• Partner with business units to translate strategies and OKRs into capability- and outcome-based architecture roadmapsthat must with fully rationalized financials and an applied knowledgeof,rather than project-specificsolutions. In clinical operations, this includes collaborating with trial operations, site engagement, patient recruitment, and data management leaders to build roadmaps thatoptimizestudy start-up timelines, site activation efficiency, patient enrollment velocity, and data quality.

• Providean enterprise-wide view of interrelated business and technical capabilities,identifyingpatterns, shared needs, and reusable platforms and services. InClinical Operations contexts, surface opportunities toconsolidatedisparate site management tools, EDC platforms, and patient data systems, andidentifywhere agentic AI and automation can reduce manual operational burden.

• Guide senior stakeholders through architectural options, trade-offs, and investment implications using clear, business-focused narratives and models. For clinical initiatives, articulate how architecture decisions impact trial timelines, regulatory risk, site partner experience, and patient enrollment.

• Ability to translateclinical domainobjectives(study, regulatory requirements, and site/patient operational constraints)into reusable capability models and architectural blueprints that enable consistent, scalable trial delivery across geographies and therapeutic areas.

• Use enterprise architecture tools (e.g.,LeanIX,Ardoq, MEGA) to define and maintain stable capability models and EA meta-models; map capabilities to processes, systems, products, outcomes, and key data domains; and support intake of new ideas into the enterprise roadmap through formalized architecture governance and portfolio intake processesand manage financial health across the portfolioIn clinical domains, use capability models to organize trial operations (study design, site management, patient cohort management, data collection, compliance, closeout) and map them to technology investments and data flows.

• Govern and rationalize the EA application and tooling portfolio, including inventories of business, data, and technology assets, and promote consistent adoptionof standardsacross the organization. In clinical domains, rationalize point solutions and duplicate site/patient management tools;establishgovernance for new clinical technology investments to ensure alignment with reference architectures.

• Collaborate with otherbusiness leaders, productmanagers,and domain architects and technology leaders toidentifyand mature shared services, platforms, and common patterns. Specifically,partnerswith clinical domain architects and product teams to evolve and standardize architectures for site engagement, patient recruitment, trial data management, and regulatory compliance automation.

• Monitor technology and industry trends (especially AI/ML, data platforms,lakehousegovernancepatterns, life sciences tech, clinical trial innovation, and agentic AI applications in clinical workflows) and incorporate relevant innovations into enterprise standards and roadmaps. Track emerging capabilities in decentralized trials, wearable data integration, AI-driven patient matching, and agent-based workflow automation to keep IQVIA's ClinicalOperationsarchitecture competitive.

• Mentor and influence architects and senior engineers to raise architecture maturity and adherence to enterprise standards across delivery teams. Develop coaching and reference architectures that enable clinical product and platform teams to build scalable, interoperable solutions aligned to enterprise standards.

Skills andExperience

• 15+ years in software development with 10 612+ years in enterprise architecture in large, complex organizations.

• Demonstrated experience owning enterprise-wide technology strategies and roadmaps, including business architecture, value streams, capability maps, and customer journeysand apply financial acumen to ensure health of the portfolio

• Recent, relevant enterprise experience with applied data science, AI/ML, and agentic AI solutions, including designing architectures for LLM-based and agent-based systems using technologies such as vector databases (e.g., Pinecone, Redis), orchestration frameworks (e.g.,Lang Chain), andMLOpsplatforms (e.g.,MLflow, Azure ML). Specific to clinical domains: hands-on experience with AI/ML applications in patient cohort discovery, site feasibility modeling, protocol complexity assessment, or operational forecasting for trial success.

• Strong enterprise data architecture background, including implementation of datalakehousearchitectures on platforms such as Databricks and Snowflake using medallion layering, plus data governance platforms and automation, data catalogs, ontologies, and taxonomies. In clinical contexts:demonstratedexperience architecting clinical datawarehouses, data warehouses, dataintegration, harmonized patient and site data models, and regulatory-compliant data governance for clinical trial data.

• Deep, hands-on familiarity with clinical operations and clinical trial management, including study design, regulatory pathways, site activation and management, patient recruitment and cohort identification, workflows, protocol adherence monitoring, safety and pharmacovigilance reporting, and trial closeout and data archival. Preference for candidates with direct exposure to site partner needs, patient engagement challenges, and operational constraints that shape how technology canoptimizetrial delivery.

• Experience in healthcare or life sciences, with a strong preference for working closely with clinical trial management, clinical operations, or related domains. Candidates should have directly supported ClinicalOperations functions (site operations, patient recruitment, data management, regulatory compliance) and understand how technology architecture decisions cascade into operational efficiency, regulatory risk, and trial outcomes.

• Deep understanding of modern architecture styles (event-driven, microservices-based, RESTful and alternative integration patterns, API-first) and how to codify them as enterprise standards and referencearchitectures. For clinical domains: ability to apply these patterns to site management workflows, patient data orchestration, and real-time trial monitoring dashboards.

• Experience with both on-premises and cloudarchitectureon Azure and/or AWS.

• Advanced proficiency with enterprise architecture tools (e.g.,LeanIX,Ardoq, MEGA, or equivalent) and expertise in EA meta-models, capability modeling, portfolio management, data and application inventories, and architecture governance; demonstrated ability to design and operationalize EA meta-models that organize business capabilities, technology assets, data domains, and integration patterns at enterprise scale. For clinical applications: proven skill in building capability models that reflect trial operations, site partner experience, and patient journeys, enabling consistent translation ofClinical Operations strategyinto technology roadmaps.

• Soft skills should includestrong executivepresence,articulate communicationand influence skills,collaboration, andtenacity witha track recordof partnering with senior business, technology, and product leaders to drive adoption ofstandard-driven enterprise architectures at scale. Specifically, ability to engage clinical operations executives, site partners, patient advocates, and regulatory stakeholders to build consensus on architecture directions anddemonstratehow technology investments drive operational and patient outcomes.