Principal Data & Analytics Architect

Cigna Group•Austin, NJ

1d•Remote

About The Position

The Principal Data & Analytics Architect is a senior technology leader responsible for shaping the company's data, analytics, and AI strategy. This role works closely with business and technology leaders to design solutions that help teams make better decisions using trusted data. The person in this role develops long-term plans for data and analytics platforms, promotes best practices, and supports innovation across the organization. This is an individual contributor role that requires strong leadership, strategic thinking, and the ability to influence teams and leaders across the enterprise.

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
12+ years of experience in data architecture, enterprise architecture, data engineering, analytics, or related technology roles.
Experience creating enterprise-wide data and analytics strategies and technology roadmaps.
Strong knowledge of modern data platforms and cloud technologies.
Experience working in large, complex, and regulated organizations.
Strong communication and leadership skills with the ability to influence decision-making across multiple teams.
Experience with Cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP)
Experience with Data lakehouse, data mesh, or data fabric architectures
Experience with API and event-driven architectures
Experience with Data governance, security, privacy, and compliance frameworks
Experience with AI, machine learning, and advanced analytics technologies

Nice To Haves

Experience leading enterprise data transformation initiatives.
Experience supporting AI-enabled business solutions.
Experience within healthcare, insurance, financial services, or other regulated industries.
Experience developing architecture standards and mentoring technical teams.

Responsibilities

Develop and maintain the company's data and analytics architecture strategy and future-state roadmap.
Design scalable data platforms that support reporting, analytics, artificial intelligence (AI), and machine learning (ML).
Create standards and best practices for collecting, integrating, and sharing data.
Partner with business and technology teams to align data solutions with company goals.
Support self-service reporting, business intelligence, and advanced analytics capabilities.
Ensure data solutions meet security, privacy, compliance, and governance requirements.
Establish architecture standards, design patterns, and reusable solutions across the enterprise.
Evaluate emerging technologies and recommend opportunities to improve data and analytics capabilities.
Guide architecture decisions for large-scale data and analytics initiatives.
Promote modern practices such as DataOps, MLOps, automation, and cloud-based data solutions.
Work with engineering and product teams to deliver scalable, reliable, and cost-effective solutions.
Mentor technical teams and share architecture best practices across the organization.