# Architecture Principal – Data & Analytics

**Company**: Evernorth Health Services
**Location**: Hyderabad, India
**Experience**: senior
**Job type**: full-time
**Category**: Data Science
**Industry**: Healthcare

**Apply**: https://cigna.wd5.myworkdayjobs.com/en-US/cignacareers/job/Hyderabad-India/Architecture-Principal---Data---Analytics---HIH---Evernorth_26013521?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/architecture-principal-data-and-analytics-2e77ff63-4f9/

## Description

The Architecture Principal – Data & Analytics 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.

**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.

**Key Responsibilities**

### Strategy & Architecture Leadership

- 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.

### Data Platform & Analytics Architecture

- Architect modern data platforms (cloud 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.

### Data Governance, Privacy & Compliance

- 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.

### Innovation & Emerging Capabilities

- 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.

### Governance & Decision Enablement

- 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.

### Delivery Partnership & Enablement

- 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).

### Talent & Community Leadership

- Serve as a mentor and thought leader across the architecture and data community.

- Drive adoption of best 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 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)

- Cloud ecosystems (Azure, AWS, GCP)

- APIs, event-driven architecture, and streaming

- Data governance, security, and privacy frameworks

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## Skills

### Required
- Modern data platforms
- Cloud ecosystems
- APIs
- event-driven architecture
- streaming
- Data governance
- security
- privacy frameworks
- AI/ML
- GenAI
- agentic analytics
- intelligent automation

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