SENIOR DATA ARCHITECT (Data Modelling & Azure AI; Enterprise AI & Data Centre of Excellence)

Requisition #: R26-3627 (RQ00239)

Location: Hybrid (3 days onsite / 2 days WFH; Toronto, ON - *See Work Model)

Engagement Type: Contract

Number of Resources required: 1

Term: 2026-11-23 to 2027-05-23 (130 days) with possible extension

Rate (CAD): Up to $102.00 per hour / Commensurate with related experience and market competitiveness

Hours per day: 7.25

Security Screening: Standard (Criminal Record Check)

Tri-global Solutions Group Inc. is seeking one (1) Senior Data Architect/Modeller to join our talented Service Delivery team within Metrolinx.

WORK MODEL: The successful contractor will be working hybrid with 3 days in office at 277 Front Street West, Toronto, Ontario and 2 days remote/work from home per week.

Thank you.

Tri-global Solutions Group Inc.

Website: https://tri-global.com

PROJECT OVERVIEW

The Senior Data Architect/Modeller will design and evolve enterprise data architecture and data models to enable scalable analytics, AI, and data products. The role will help establish the future-state data architecture, identify critical data assets, and define standards and integration patterns that enable data to be governed, reusable, accessible, and AI-ready.

DESCRIPTION OF SERVICES

Key Responsibilities

- Design and maintain enterprise data architecture and conceptual, logical, and physical data models supporting AI, analytics, and operational use cases.
- Define scalable architecture patterns for the integration, storage, transformation, sharing, and consumption of enterprise data.
- Design reusable data products and common data models that can support multiple business and AI use cases.




- Contribute to the organization’s future-state data architecture, including transition from existing platforms and architectures.
- Identify and define critical data assets and domains required to support enterprise priorities.
- Establish and promote enterprise data architecture, modelling, interoperability, and integration standards.
- Partner with Data Governance teams to embed data ownership, quality, metadata, lineage, classification, and lifecycle requirements into architecture and data products.
- Assess data requirements and architecture implications for AI, Generative AI, machine learning, advanced analytics, and reporting initiatives.
- Work with business, Data & AI, architecture, engineering, and technology teams to translate business requirements into scalable data solutions.
- Identify architecture gaps, duplication, data silos, and opportunities to improve data reuse and interoperability across the enterprise.

QUALIFICATIONS & EXPERIENCE

- Degree in Computer Science, Information Systems, Data Management, Engineering, or a related discipline, or equivalent experience.
- Significant experience in enterprise data architecture, data modelling, data engineering, or related disciplines.
- Demonstrated experience developing conceptual, logical,



and physical data models and enterprise data architectures.
- Experience designing contemporary data architectures supporting cloud, analytics, AI/ML, and enterprise integration.
- Strong knowledge of data modelling, data integration, APIs, data platforms, metadata, master/reference data, and data quality concepts.
- Understanding of data governance, data ownership, lineage, security, privacy, and information lifecycle management.
- Knowledge of modern architecture approaches such as data lakehouse, data products, domain-oriented architecture, and cloud-based data platforms.
- Ability to translate complex business and technical requirements into practical architecture standards, models, and patterns.
- Strong stakeholder management, communication, documentation, and problem-solving skills.

MANDATORY REQUIREMENTS (Candidates must meet all requirements below)

- Significant experience designing enterprise data architectures and conceptual, logical, and physical data models for AI/ML, Generative AI, analytics, and cloud workloads, including the data requirements for model training, inference, RAG, feature engineering, and AI/ML pipelines.
- Deep technical expertise in up-to-date cloud data platforms, data engineering, integration, APIs, metadata, lineage, and data quality, with strong knowledge of the Azure data and AI ecosystem, Azure Machine Learning, and Microsoft Foundry/Azure AI Foundry, and architectural patterns supporting scalable AI/ML solutions.
- Strong understanding of data governance, data ownership, lineage, data quality, security, privacy, and information lifecycle management, with the ability to design

📌 Senior Data Architect (Toronto)
🏢 Tri-global Solutions Group
📍 Toronto