Enterprise Data and AI Architect, Vice President

Overview

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long‑term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career. Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.

The Enterprise Data & AI Architect will lead the design and evolution of scalable, secure, and governed architectures that support analytics, operational workloads, and AI‑driven innovation. This role spans data platforms, integration, semantic modeling, AI foundations, and enterprise governance
, enabling consistent, reusable capabilities across the organization.

This position supports multiple architect tracks
, and candidates will be aligned based on their strengths and experience:

• Data Platform Architecture
• Cloud Data & Integration Architecture
• AI & Data Architecture
• Knowledge / Semantic Architecture
• Data Product & Information Architecture
• Enterprise Data Architecture

• Data Platform & Integration Architecture
  • Design scalable enterprise data platforms (lakehouse, data warehouse, streaming, ingestion layers)
  • Define modern integration patterns:
    • ETL / ELT
    • Change Data Capture (CDC)
    • APIs and event‑driven architectures
  • Drive platform modernization, interoperability, and data movement strategies
• AI & Knowledge Architecture
  • Architect AI‑ready data foundations for analytics, machine learning, and generative AI
  • Define and implement:
    • Semantic models
    • Ontologies
    • Metadata standards
    • Knowledge graph frameworks
  • Enable advanced AI use cases including:
    • Retrieval‑Augmented Generation (RAG)
    • Semantic search
    • Explainable AI patterns
• Information & Data Product Architecture
  • Design business‑aligned data products and reusable data assets
  • Define architectures for:
    • Metadata management
    • Data lineage
    • Data quality and governance
  • Enable trusted, discoverable, and reusable data ecosystems
• Enterprise Architecture & Governance
  • Establish architecture standards, patterns, and reference models
  • Participate in Architecture Review Boards (ARB) and governance processes
  • Ensure alignment with enterprise strategy, risk, and compliance requirements
• Architecture Enablement & Collaboration
  • Partner across engineering, cloud, AI, and governance teams
  • Develop reusable:
    • Architecture templates
    • Standards and guidelines
    • Onboarding frameworks
  • Provide hands‑on guidance to delivery teams across platforms

• 8+ years of experience in:
  • Data Architecture
  • Platform Architecture
  • AI Architecture or related fields
• Proven experience designing enterprise‑scale data platforms and integration solutions
• Strong expertise in:
  • Data storage, processing, and integration architectures
  • Cloud platforms (AWS, Azure, or GCP)
  • Modern data paradigms (lakehouse, warehouses, APIs, event‑driven systems)
• Demonstrated ability to translate business requirements into scalable architectures
• Strong communication and stakeholder engagement skills
• Experience working in cross‑functional enterprise environments

• Data Platform & Integration
  • ETL / ELT, CDC, streaming, APIs
  • Scalability, performance optimization, resiliency
• AI & Data Architecture
  • AI / ML, Generative AI, RAG
  • AI‑ready data foundations and MLOps alignment
• Knowledge & Semantic Architecture
  • Ontologies, knowledge graphs, semantic modeling
  • Metadata, lineage, and AI trust frameworks
• Information & Data Product Architecture
  • Data products and domain‑aligned data models
  • Metadata strategy and data governance
• Enterprise Data Architecture
  • Architecture standards, operating…