Senior Data Architect/Modeller - Toronto

We are seeking an experienced Senior Data Architect/Modeller to design, evolve, and implement enterprise data architecture and comprehensive data models that enable scalable analytics, artificial intelligence, and reusable data products. In this role, you will help establish future-state data architecture, identify critical enterprise data assets, and define standards and integration patterns that ensure data is governed, accessible, traceable, and AI-ready. Leveraging modern cloud architectures and the Azure Data and AI ecosystem, you will design conceptual, logical, and physical data models supporting AI/ML pipelines, Generative AI workloads, Retrieval-Augmented Generation (RAG), feature engineering, and advanced analytical solutions.
Location: Toronto, ON (Hybrid – 3 days a week onsite)
Duration: 5-month contract.
Advantages
Next-Gen AI & Cloud Focus: Architect advanced data models for Generative AI, RAG, and Azure AI Foundry solutions.
Modern Architecture Patterns: Drive adoption of modern lakehouse and domain-oriented reusable data products.
Enterprise-Level Visibility: Define future-state data standards and frameworks across the broader organization.
Hybrid Work Flexibility: Enjoy a balanced hybrid work schedule with 3 days onsite in Toronto.
Responsibilities
Design and maintain enterprise data architectures and conceptual, logical, and physical data models supporting AI, machine learning, analytics, and operational systems.
Define scalable architectural patterns for enterprise data integration, storage, transformation, sharing, and consumption across cloud platforms.
Design reusable data products and common canonical data models capable of supporting multiple business and AI/ML use cases.
Formulate and execute roadmap strategies for transition from existing legacy platforms to modern future-state architectures.
Identify and categorize critical enterprise data assets, entities, and subject areas aligned with strategic organizational priorities.
Establish, document, and champion enterprise data architecture, data modeling, interoperability, and API integration standards.
Collaborate closely with Data Governance teams to embed data ownership, quality controls, metadata standards, data lineage, classification, and lifecycle management into all architectural deliverables.
Assess data requirements and architectural implications for AI, Generative AI, machine learning, RAG frameworks, and feature stores.
Partner with engineering, architecture, analytics, and business stakeholders to translate complex requirements into scalable, practical data solutions.
Identify architectural gaps, redundant data pipelines, and data silos to foster enhanced interoperability and data reuse across the enterprise.
Qualifications
AI/ML & Enterprise Data Architecture: Significant experience designing enterprise data architectures and conceptual, logical, and physical data models tailored for AI/ML, Generative AI, advanced analytics, and cloud workloads, including model training, inference, RAG, feature engineering, and AI/ML pipelines (Strictly Required).
Cloud Platforms & Azure AI Ecosystem: Deep technical expertise in modern cloud data platforms, data engineering, APIs, metadata management, and lineage, with strong practical knowledge of the Azure Data & AI ecosystem, Azure Machine Learning, and Microsoft Foundry / Azure AI Foundry (Strictly Required).
Data Governance & Lifecycle Management: In-depth understanding of enterprise data governance, data ownership, lineage, quality frameworks, security, privacy, and information lifecycle management to support fit-for-purpose model lifecycles (Strictly Required).
Modern Architectural Paradigms: Hands‑on experience with modern data concepts such as data lakehouses, domain‑driven design, data mesh, and reusable data products (Strictly Required).
Cross-Functional Translation: Demonstrated ability to translate complex technical and business requirements into concrete architectural standards, blueprints, and data models (Strictly Required).
Education & Professional Background: Degree in Computer Science, Information Systems, Data Management, Engineering, or a related discipline, or equivalent professional experience (Strictly Required).
Nice-to-Have Assets
Prior enterprise data architecture or data modeling experience within the public sector.
Relevant cloud or architecture certifications (e.G., Azure Solutions Architect, Azure Data Engineer, TOGAF, CDMP).
Hands‑on knowledge of master data management (MDM) tools and data catalog platforms.
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming;
Indigenous or Aboriginal Peoples;
persons with disabilities (visible or invisible) and;
members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to View email address on ca.hrm.tc to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
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