Sr Principal Enterprise Data Architect, AI

Sr Principal Enterprise Data Architect responsible for shaping, governing, and advancing the enterprise data architecture strategy, with a strong focus on enabling analytics, AI, and emerging intelligent capabilities. This role guides the architectural design and validation of AI enabled solutions, including analytics accelerators, intelligent assistants, and data driven platforms, and supports the transition of successful pilots into production.

What you'd actually do

  1. Develop, maintain, and communicate the enterprise data architecture blueprint, including data models, platforms, integration patterns, standards, and policies.
  2. Define and evolve the enterprise data strategy to support analytics, business intelligence, AI/ML, and generative AI initiatives.
  3. Partner with business and technology teams to identify high impact opportunities where data and AI can improve decision making, streamline workflows, or unlock new enterprise capabilities.
  4. Guide the architectural design and validation of AI enabled solutions, including analytics accelerators, intelligent assistants, and data driven platforms.
  5. Lead and evolve data governance practices, including metadata management, data quality, lineage, classification, and stewardship.

Skills

Required

  • Extensive experience in data architecture, data engineering, or enterprise architecture, with leadership responsibility in large scale, complex environments.
  • Proven ability to translate business strategy into actionable architectural direction and enterprise roadmaps.
  • Strong background in enterprise data platforms, including cloud-based data lakes, warehouses, and integration architectures.
  • Solid understanding of AI and generative AI concepts, architectures, and enablement patterns, including how data architecture supports these capabilities.
  • Demonstrated success influencing senior leaders and cross functional teams without direct authority.
  • Exceptional communication skills

Nice to have

  • cloud native data architectures and platforms
  • hybrid and multi cloud hosting environments
  • data mesh/fabric
  • real time analytics

What the JD emphasized

  • strong focus on enabling analytics, AI, and emerging intelligent capabilities
  • strong focus on enabling analytics, AI, and emerging intelligent capabilities
  • architectural design and validation of AI enabled solutions
  • architectural design and validation of AI enabled solutions
  • data architecture supports these capabilities

Other signals

  • enterprise data architecture strategy
  • enabling analytics, AI, and emerging intelligent capabilities
  • architectural design and validation of AI enabled solutions
  • data architecture supports these capabilities