RQ00239 – Senior Data Architect/Modeller

S M Software Solutions Inc; Toronto; Hybrid; CAD 110.000 - 150.000; Vollzeit

Zusammenfassung

Metrolinx is seeking a Senior Data Architect/Modeller to design and evolve enterprise data architectures for analytics, AI, and data products. The role focuses on scalable, governed data models, Azure data/AI tooling, and data governance integration across teams.

Hybrid work arrangement with onsite days in Toronto, start Nov 23, 2026 and end Apr 23, 2027, supporting enterprise initiatives and AI-driven data platforms.

Qualifikationen

• Significant experience designing enterprise data architectures and models for AI/ML and cloud workloads.
• Deep knowledge of Azure data and AI technologies and data governance concepts.
• Ability to translate requirements into scalable, governed data architectures.

Aufgaben

• Design and evolve enterprise data architecture and data models to enable AI, analytics, and data products.
• Define reusable data models and architecture standards for scalable AI-ready data solutions.
• Collaborate with governance teams to embed data ownership, quality, and lineage.
• Assess architecture implications for AI/Generative AI, ML, and reporting initiatives.
• Translate business requirements into scalable data solutions across platforms.

Kenntnisse

Data architecture

Data modelling

Azure ecosystem

AI/ML pipelines

Data governance

Ausbildung

Degree in CS/IS/Engineering

Jobbeschreibung

Client: Metrolinx – RQ00239

We are seeking an experienced Senior Data Architect/Modeller with significant expertise in enterprise data architecture, conceptual, logical, and physical data modelling, cloud data platforms, data engineering, and AI/ML solutions. The ideal candidate will have strong knowledge of modern Azure data and AI technologies, including Azure Machine Learning and Microsoft Foundry/Azure AI Foundry, along with expertise in data governance, metadata, data lineage, integration, and data quality. The successful candidate will play a key role in designing and evolving enterprise data architecture, establishing reusable data models and architecture standards, and enabling scalable, governed, and AI-ready data solutions across the organization.

Role Snapshot

• Job Title: RQ00239 – Senior Data Architect/Modeller
• Client: Metrolinx
• Work Location: 277 Front Street West, Toronto, Ontario, Canada, M5V 2X4
• Work Arrangement: Hybrid – 3 Days per Week Onsite
• Start Date: November 23, 2026
• End Date: April 23, 2027
• Business Days: 110.00
• Hours: 7.25 hours per day
• Public Sector Experience: Preferred but not required

Must Have

• 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 modern 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 governed, traceable, and fit-for-purpose data architectures that support the AI/ML and model lifecycle.

Description

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.

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 modern 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 lake house, 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.