Job Summary: The Senior Data Architect/Modeller will lead the design and evolution of enterprise data architecture and models to support scalable analytics, AI, and data products.

This role focuses on establishing future-state data architectures, defining standards, and ensuring data assets are governed, reusable, accessible, and AI-ready within a hybrid work environment in Toronto.

Responsibilities: Design and maintain enterprise data architecture and data models for AI, analytics, and operational use cases.

Define scalable architecture patterns for data integration, storage, transformation, sharing, and consumption.

Create reusable data products and common data models supporting multiple business and AI use cases.

Contribute to future-state data architecture and transition from existing platforms.

Identify and define critical data assets and domains aligned with enterprise priorities.

Establish and promote data architecture, modelling, interoperability, and integration standards.

Partner with Data Governance teams to embed ownership, quality, metadata, lineage, classification, and lifecycle requirements.

Assess data requirements and architecture implications for AI, Generative AI, machine learning, advanced analytics, and reporting.

Collaborate with business, Data & AI, architecture, engineering, and technology teams to translate requirements into scalable data solutions.

Identify architecture gaps, data silos, and opportunities to improve data reuse and interoperability.

Required Skills: Proven experience in enterprise data architecture and data modelling for AI/ML, Generative AI, analytics, and cloud workloads.

Expertise in designing conceptual, logical, and physical data models and architectures.

Strong knowledge of modern cloud data platforms, especially Azure data and AI ecosystem, Azure Machine Learning, and Microsoft Foundry/Azure AI Foundry.

Deep understanding of data integration,



APIs, metadata, lineage, and data quality.

Solid grasp of data governance, ownership, lineage, security, privacy, and information lifecycle management.

Ability to design governed, traceable, and fit-for-purpose data architectures supporting AI/ML lifecycle.

Excellent stakeholder management, communication, documentation, and problem-solving skills.

Desired Skills: Experience with data lakehouse and domain-oriented architecture approaches.

Familiarity with cloud-based data platform innovations and scalable AI/ML architectural patterns.

Knowledge of advanced analytics and reporting architecture implications.

Experience working in hybrid work environments and cross-functional teams.

Rated Criteria: Enterprise Data Architecture Design - 30 Points AI/ML and Generative AI Data Modelling Expertise - 25 Points Cloud Data Platforms and Azure Ecosystem Knowledge - 20 Points Data Governance and Security Compliance - 15 Points Stakeholder Management and Communication - 10 Points Total: 100 Points Deliverables: Comprehensive enterprise data architecture frameworks and models.

Reusable data products and common data models for business and AI use cases.

Documentation of architecture standards, integration patterns, and governance policies.

Transition plans for migrating to future-state data platforms.

Assessment reports on data requirements and architecture implications for AI and analytics initiatives.

Must Haves: Extensive experience designing enterprise data architectures and models supporting AI/ML pipelines and cloud workloads.

Deep technical expertise in Azure data and AI technologies, including Azure Machine Learning and Microsoft Foundry/Azure AI Foundry.

Strong knowledge of data governance, lineage, quality, security, and privacy principles.

Proven ability to create governed, traceable, and scalable data architectures aligned with AI/ML lifecycle needs.

Public Sector Experience: Preferred

📌 Senior Data Architect (Ontario)
🏢 vTech Solution
📍 Ontario