Enterprise Architecture Senior Principal – Data, APIs, and Integration Architecture

The Enterprise Architecture - Data Architecture Senior Principal is a Band 5 Senior Contributor responsible for defining and advancing the enterprise data and analytics architecture strategy, target states, and multi-year roadmaps across the organization. This role serves as a recognized architecture authority , setting the northstar vision for modern data platforms, analytics, and AI-enabled capabilities—translating business priorities into pragmatic, scalable, and future-ready architectures .

Operating with high enterprise influence and no direct reports, this role requires strong executive presence, the ability to influence without authority, and a relentless focus on enabling data-driven decision making, hyper-personalization, and AI-first innovation .
Key Outcomes

• Enterprise Data & Analytics Vision: Define and publish a business-aligned data and analytics architecture strategy with a clear 3–5 year roadmap covering data platforms, governance, analytics, AI/ML, and integration layers.
• Scalable & Reusable Data Foundations: Establish modern, modular data architectures that reduce fragmentation, promote reuse, and enable enterprise-scale analytics and AI.
• Decision Velocity through Architecture Governance: Implement architecture principles, guardrails, and decision frameworks to improve speed, consistency, and quality of analytics and data platform decisions.
• AI-Ready & Insights-Driven Enterprise: Enable analytics-ready data, semantic layers, and AI capabilities that accelerate insights, automation, and intelligent decisioning.
• Cross-Domain Alignment: Act as a unifying architecture leader across Digital, Data, AI, Security, and Business domains to ensure alignment on key investment and design decisions.

• Define and evolve enterprise data & analytics architecture strategy, capability maps, and target-state designs .
• Develop and maintain multi-year roadmaps aligned to business outcomes, cost optimization, and innovation priorities.
• Establish a data-as-a-product and platform-based operating model .

• Architect modern data platforms (cloud-native databases, data lakehouse, streaming, real-time pipelines, semantic/ontology layers).
• Define patterns for data ingestion, transformation, storage, access, and consumption .
• Enable self-service analytics , BI, and advanced analytics capabilities across the enterprise.
• Lead architecture for AI/ML platforms, feature stores, and model lifecycle integration .

• Define enterprise integration strategy spanning APIs, messaging, event streaming, data sharing, and intelligent orchestration.
• Establish architecture standards for API-led connectivity, event-driven architecture, service-mesh, and real-time integrations
• Define reusable integration patterns across digital channels, core platforms, data and AI platforms
• Lead architecture for enterprise interoperability including healthcare interoperability, FHIR ecosystem, and external data exchanges

• Embed data governance, quality, lineage, metadata, and stewardship frameworks into architecture design.
• Ensure architectures support regulatory, privacy, and security requirements by design .
• Establish patterns for trusted, secure, and compliant data usage .

• Drive innovation in AI/ML, GenAI, agentic analytics, and intelligent automation .
• Evaluate and guide adoption of emerging technologies (e.g., knowledge graphs, semantic models, real-time decisioning).
• Lead proof-of-concepts and pilot initiatives for next-generation analytics capabilities.

• Provide architecture leadership for high-impact data and analytics…