Enterprise Data and AI Architect, Vice President

About the role

We are building a high-impact architecture team focused on advancing enterprise data platforms, AI capabilities, and information architecture at scale. 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.

Key Responsibilities

• 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

Required Qualifications

• 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

Areas of Specialization (One or More)

• 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 models, and governance, ARB participation and capability frameworks

Preferred / Nice To Have Experience

• With modern platforms such as: Snowflake, Databricks
• Exposure to: Data mesh or federated data models
• Experience in regulated environments (e.g., financial services)
• Familiarity with: Metadata platforms, Governance tooling
• Knowledge of: Infrastructure-as-Code, CI/CD, MLOps practices