Job DescriptionJob Description

Job Title: Data Architect - Senior

Location: Toronto, ON

Work Model: Hybrid

Duration: 5 months

Must Haves

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

Description / Responsibilities / Skills

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





- 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.
- Identify architecture gaps, duplication, data silos, and opportunities to improve data reuse and interoperability across the enterprise.

Experience & Skill Set Requirements

Qualifications & Experience

- Degree in Computer Science, Information Systems, Data Management, Engineering, or a related discipline, or equivalent experience.
- 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.

Public Sector Experience

- Public Sector Experience: preferred but not required

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