RQ00239 – Senior Data Architect/Modeller
- Toronto, ON, Canada
Hybrid
Internship
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Original job description
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
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
If you are interested and your profile matches the requirements, kindly submit the following mandatory documents to hrsmss@smsoftconsulting.com by Monday, November 9, 2026, at 8:00 AM EST.
Mandatory Documents
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Additional Information
You have received this message either as a result of contacting our company to express interest in employment or as a result of posting your resume in a location that can be accessed by recruiters or HR specialists, which suggests an interest in being contacted about employment opportunities.
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
- 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.
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.
- 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.
If you are interested and your profile matches the requirements, kindly submit the following mandatory documents to hrsmss@smsoftconsulting.com by Monday, November 9, 2026, at 8:00 AM EST.
Mandatory Documents
- Updated Resume in Word format (Mandatory)
- Skills Matrix and References (Mandatory)
- Expected Hourly Rate (Mandatory)
- Visa Status (Mandatory)
- LinkedIn ID (Mandatory)
WhatsApp Group
For daily job updates, you can also join our WhatsApp group using the link below:
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Additional Information
- Work Arrangement: Hybrid.
- Public Sector Experience: Preferred but not required.
You have received this message either as a result of contacting our company to express interest in employment or as a result of posting your resume in a location that can be accessed by recruiters or HR specialists, which suggests an interest in being contacted about employment opportunities.
More about this job
Responsibilities
Design and evolve enterprise data architecture, data models, reusable data products, and integration standards to support analytics, AI/ML, operational use cases, and the organization’s future-state architecture. Partner with governance, business, data, architecture, and engineering teams to embed data ownership, quality, metadata, lineage, security, and lifecycle requirements while identifying opportunities to improve data reuse and interoperability.
Requirements
Requires significant experience in enterprise data architecture, data modeling, data engineering, and cloud-based architectures supporting analytics, AI/ML, and enterprise integration. Candidates should have strong knowledge of Azure data and AI technologies, data governance and quality, metadata, lineage, security, and privacy, as well as the ability to translate business and technical needs into practical architecture standards and models.
Skills
- Enterprise Data Architecture
- Conceptual, Logical, And Physical Data Modeling
- Cloud Data Platforms
- Data Engineering
- Azure Machine Learning
- Microsoft Foundry/Azure AI Foundry
- AI/ML Architecture
- Generative AI
- Data Governance
- Data Integration
- APIs
- Metadata And Data Lineage
- Data Quality
- Data Products
- Data Security And Privacy
- Stakeholder Management
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Government & Public Sector
- Consulting
Keywords
- Enterprise Data Architecture
- Conceptual Data Modeling
- Logical Data Modeling
- Physical Data Modeling
- Azure
- Azure Machine Learning
- Microsoft Foundry
- Azure AI Foundry
- Cloud Data Platforms
- Data Engineering
- Artificial Intelligence
- Machine Learning
- Generative AI
- Retrieval-Augmented Generation
- Feature Engineering
- AI/ML Pipelines
- Data Governance
- Data Ownership
- Data Quality
- Metadata
- Data Lineage
- Data Integration
- APIs
- Master Data
- Reference Data
- Data Lakehouse
- Data Products
- Domain-Oriented Architecture
- Enterprise Integration