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

Cigna Healthcare•St. Louis, MO

2d•$174,800 - $291,300•Remote

About The Position

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.

Requirements

Bachelor’s degree in computer science, Engineering, or related field.
12+ years of experience in enterprise architecture, data engineering, or analytics platforms.
Proven success defining data/analytics architecture strategies, target states, and roadmaps.
Deep experience in large-scale, regulated enterprise environments (e.g., healthcare, financial services).
Strong ability to influence senior stakeholders without direct authority.
Expertise in: Modern data platforms (Lakehouse, Data Mesh, Data Fabric)
Expertise in: Cloud ecosystems (Azure, AWS, GCP)
Expertise in: APIs, event-driven architecture, and streaming
Expertise in: Data governance, security, and privacy frameworks
Expertise in: AI/ML and advanced analytics platforms

Responsibilities

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.
Establish modern, modular data architectures that reduce fragmentation, promote reuse, and enable enterprise-scale analytics and AI.
Implement architecture principles, guardrails, and decision frameworksto improve speed, consistency, and quality of analytics and data platform decisions.
Enable analytics-ready data, semantic layers, and AI capabilities that accelerate insights, automation, and intelligent decisioning.
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 initiatives.
Establish reference architectures, reusable patterns, and standards for enterprise adoption.
Drive alignment across portfolios to reduce duplication and optimize investments.
Partner with engineering, product, and data teams to ensure architectures are executable, scalable, and cost-efficient.
Enable adoption of modern engineering practices (DataOps, MLOps, CI/CD for data).
Support vendor/platform strategy (e.g., lakehouse, cloud, third-party integrations).
Serve as a mentor and thought leader across the architecture and data community.
Drive adoption of best practices, patterns, and architectural discipline.