TheArchitecture Principal – Data Analytics is aBand 5 Senior Contributor responsible for defining and advancing theenterprise data and analytics architecture strategy, target states, and multi-year roadmaps across the organization. This role serves as arecognized architecture authority, setting thenorthstar vision for modern data platforms, analytics, and AI-enabled capabilities—translating business priorities intopragmatic, 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 enablingdata-driven decision making, hyper-personalization, and AI-first innovation.
Key Outcomes
- Enterprise Data Analytics Vision: Define and publish abusiness-aligned data and analytics architecture strategy with a clear3–5 year roadmap covering data platforms, governance, analytics, AI/ML, and integration layers.
- Scalable Reusable Data Foundations: Establishmodern, modular data architectures that reduce fragmentation, promote reuse, and enable enterprise-scale analytics and AI.
- Decision Velocity through Architecture Governance: Implementarchitecture principles, guardrails, and decision frameworks to improve speed, consistency, and quality of analytics and data platform decisions.
- AI-Ready Insights-Driven Enterprise: Enableanalytics-ready data, semantic layers, and AI capabilities that accelerate insights, automation, and intelligent decisioning.
- Cross-Domain Alignment: Act as a unifying architecture leader acrossDigital, Data, AI, Security, and Business domains to ensure alignment on key investment and design decisions.
Key Responsibilities
Strategy Architecture Leadership
- Define and evolveenterprise data analytics architecture strategy, capability maps, and target-state designs.
- Develop and maintainmulti-year roadmaps aligned to business outcomes, cost optimization, and innovation priorities.
- Establish adata-as-a-product and platform-based operating model.
Data Platform Analytics Architecture
- Architectmodern data platforms (cloud data lakehouse, streaming, real-time pipelines, semantic/ontology layers).
- Define patterns fordata ingestion, transformation, storage, access, and consumption.
- Enableself-service analytics, BI, and advanced analytics capabilities across the enterprise.
- Lead architecture forAI/ML platforms, feature stores, and model lifecycle integration.
Data Governance, Privacy Compliance
- Embeddata governance, quality, lineage, metadata, and stewardship frameworks into architecture design.
- Ensure architectures supportregulatory, privacy, and security requirements by design.
- Establish patterns fortrusted, secure, and compliant data usage.
Innovation Emerging Capabilities
- Drive innovation inAI/ML, GenAI, agentic analytics, and intelligent automation.
- Evaluate and guide adoption of emerging technologies (e.g., knowledge graphs, semantic models, real-time decisioning).
- Leadproof-of-concepts and pilot initiatives for next-generation analytics capabilities.
Governance Decision Enablement
- Provide architecture leadership forhigh-impact data and analytics initiatives.
- Establishreference architectures, reusable patterns, and standards for enterprise adoption.
- Drive alignment across portfolios to reduce duplication and optimize investments.
Delivery Partnership Enablement
- Partner with engineering, product, and data teams to ensure architectures areexecutable, scalable, and cost-efficient.
- Enable adoption ofmodern engineering practices (DataOps, MLOps, CI/CD for data).
- Support vendor/platform strategy (e.g., lakehouse, cloud, third-party integrations).
Talent Community Leadership
- Serve as amentor and thought leader across the architecture and data community.
- Drive adoption ofbest practices, patterns, and architectural discipline.
Qualifications
Required Skills Experience
- Bachelor’s degree in computer science, Engineering, or related field.
- 18 years of experience in enterprise architecture, data engineering, or analytics platforms.
- Proven success definingdata/analytics architecture strategies, target states, and roadmaps.
- Deep experience inlarge-scale, regulated enterprise environments (e.g., healthcare, financial services).
- Strong ability toinfluence senior stakeholders without direct authority.
- Expertise in:
- Modern data platforms (Lakehouse, Data Mesh, Data Fabric)
- Cloud ecosystems (Azure, AWS, GCP)
- APIs, event-driven architecture, and streaming
- Data governance, security, and privacy frameworks
AI/ML and advanced analytics platforms
About Evernorth Health Services
Evernorth Health Services, a division of The Cigna Group, creates pharmacy, care and benefit solutions to improve health and increase vitality. We relentlessly innovate to make the prediction, prevention and treatment of illness and disease more accessible to millions of people. Join us in driving growth and improving lives.
