Principal Data Architect

Principal Data Architect

The Principal Data Architect is a leadership position responsible for developing the vision for AI-enabled data ecosystems, defining the Enterprise Data Strategy, and establishing the Data Architecture needed to realize business strategy and outcomes. This role ensures alignment of data across operational and analytical systems, enabling consistency from transaction capture through intelligent decision-making. Responsibilities include defining the vision, target state, roadmap, and governance associated with the management and use of data assets across the enterprise.

In addition, this role serves as a thought leader and is responsible for enabling advanced analytics and AI/ML technologies, as appropriate, across the company.

• Own developing, documenting the Data Strategy: Own the development and documentation of Enterprise Data Strategy by collaborating with Data Architecture, Data COE and other functional data leaders. The Data strategy verbalizes the data capabilities that we intend to create within our enterprise and the roadmap to realize it. As data capabilities span multiple areas of concern including data governance, data security, AI/ML use of data etc.
  
  the individual must have supreme communication, collaboration with ability to influence alignment, agility to achieve outcomes.
• Own Enterprise Data Architecture: By partnering with Data architecture and Enterprise architecture team and other business leaders, develop, evangelize, and govern the evolution of Data architecture within Enterprise. Data architecture includes documentation of current and target state of how data will be managed and consumed for transactional, operational, analytics use along with the right fit data technologies and their implementation patterns.
• Enable Advanced analytics and AI/ML use cases: Provide thought leadership and specific technology expertise as it relates to successful application of advanced analytics and data science techniques within the enterprise. Establish a vision for AI-enabled Data ecosystems
  , including semantic understanding and knowledge-driven architectures
• Enable effective data and analytics governance: Enable policy-driven and context-aware governance, ensuring architecture alignment to the Data strategy and overall technology strategy, principles. Assist data and analytics leaders, and business and IT leadership in developing information governance processes and structures.
• Enhance decision making: Use tools such as business information models to provide the organization with a future-state view of the information landscape that is unencumbered by the specific data implementation details imposed by proprietary solutions or technologies.
• Consult on business information modeling: Thought leadership and support for creating and managing business information models in all their forms, including conceptual models, relational database designs, message models and others.
• Secure data and analytic assets: Aid in the analysis of data and analytics security requirements and solutions, and work with the chief information security officer (CISO) and CDO to ensure that enterprise data and analytics assets are treated as a protected asset.
• Data program planning: Ensure that the architecture is used as a lens and a filter to identify, prioritize and execute the data and analytic initiatives with clear line of sight to enterprise strategies and business outcomes.

• A minimum of 12 years of professional experience in IT, including at least 5 years specializing in information and data architecture.
• Significant experience serving as a Data/Information Architect within a complex enterprise environment, with demonstrated success delivering scalable, enterprise-grade data solutions.
• Experience in the healthcare and/or insurance domain, particularly within payer organizations (e.g., insurance carriers), is highly preferred.
• Hands‑on experience with modern data and AI platforms such as Snowflake, Databricks, Azure, GCP, and/or AWS.
• Deep understanding of data technologies and the supporting infrastructure, including cloud and cybersecurity technologies, required to…