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vTech Solution Canada

Senior Data Modeller

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Dec 4, 2026
Posting language: English
Posted: Nov 4, 2026

Original job description

Job Title: Senior Data Architect/Modeller

Location: Toronto, ON

Work Model: Hybrid (3 days onsite)

Start Date: November 23, 2026

End Date: April 23, 2027

Allocation: 100%

Position Overview

We are seeking a Senior Data Architect / Modeller to design and evolve enterprise data architecture and data models that enable scalable analytics, AI, and reusable data products. This role will help define the future-state enterprise data architecture, identify critical data assets, and establish standards and integration patterns that ensure enterprise data is 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 data integration, storage, transformation, sharing, and consumption.
Design reusable data products and common data models for multiple business and AI use cases.
Contribute to the future-state enterprise data architecture, including transition from current platforms and architectures.
Identify and define critical data assets and domains aligned to enterprise priorities.
Establish and promote enterprise data architecture, modelling, interoperability, and integration standards.
Partner with Data Governance teams to embed data ownership, metadata, lineage, classification, lifecycle, and data quality requirements.
Assess data architecture needs for AI, Generative AI, machine learning, advanced analytics, and reporting initiatives.
Collaborate with business, architecture, engineering, and Data & AI teams to translate requirements into scalable data solutions.
Identify architecture gaps, duplication, silos, and opportunities for improved data reuse and interoperability.

Must-Have Skills

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

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More about this job

Responsibilities

Design and evolve enterprise data architecture, data models, integration patterns, and reusable data products for AI, analytics, and operational use cases. Define data standards and critical data assets, embed governance requirements, and collaborate across business, architecture, engineering, and Data & AI teams to improve data reuse and interoperability.

Requirements

Requires significant experience designing enterprise data architectures and conceptual, logical, and physical models for AI/ML, Generative AI, analytics, and cloud workloads. Candidates must have strong knowledge of AI data needs, cloud data platforms and engineering, Azure AI technologies, and data governance, quality, security, privacy, lineage, and lifecycle management.

Skills

Enterprise Data Architecture
Conceptual Data Modeling
Logical Data Modeling
Physical Data Modeling
AI/ML Data Requirements
Generative AI
Cloud Data Platforms
Azure Machine Learning
Microsoft Foundry / Azure AI Foundry
Data Engineering
Data Integration
APIs
Metadata and Data Lineage
Data Quality
Data Governance
Data Security and Privacy

Visa sponsorship

Not detected in the job text

Keywords

Enterprise Data Architecture
Conceptual Data Models
Logical Data Models
Physical Data Models
AI/ML
Generative AI
Model Training
Inference
Retrieval-Augmented Generation (RAG)
Feature Engineering
AI/ML Pipelines
Cloud Data Platforms
Azure
Azure Machine Learning
Microsoft Foundry
Azure AI Foundry
Data Engineering
Data Integration
APIs
Metadata
Data Lineage
Data Quality
Data Governance
Data Ownership
Data Security
Data Privacy
Data Products
Interoperability
Advanced Analytics

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