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TheSenior Data & AI Architect is a senior technical authority within Ontario One Call’s Data & Analytics function, reporting to the Director of Data Analytics & Digital Transformation. This role is responsible for defining and governing enterprise data, analytics, and AI architecture standards that support scalable data platforms, semantic layers, intelligent systems, and AI‑enabled use cases across the organization. The Senior Data & AI Architect operates within the strategic direction and governance priorities established by the Director, providing centralized design authority and architectural guardrails. The role focuses on architecture, standards, and risk management—guiding solution design, reviewing complex initiatives, and ensuring consistency, compliance, and long‑term sustainability across data and AI solutions, while enabling engineering and analytics teams to deliver effectively.

This position is located at the Guelph office located at 104 Cooper Drive, Guelph. Ontario One Call has a hybrid work model with staff dividing their workweek between in-office and at-home work per company policy.

Candidates must be able to reliably commute to the workplace during scheduled hours. Either valid driver’s license or access to reliable transportation are required.

Primary Responsibilities

- Led enterprise data and analytics architecture patterns for enterprise data ingestion, transformation, and serving layers using Microsoft Fabric, Azure Data Factory, and related platforms.
- Establish standards for batch and streaming data workflows aligned with enterprise architecture and integration principles.




- Define dimensional data modeling standards (fact and dimension structures) to support analytics, reporting, and AI workloads.
- Set expectations for data quality, validation, lineage, and observability across data pipelines.
- Guide performance, scalability, and reliability design decisions to support enterprise‑scale workloads.
- Led architecture patterns for machine learning and AI‑enabled solutions aligned with enterprise AI standards.
- Establish feature engineering and feature store design standards to support consistent training and inference.
- Guide adoption of AI orchestration patterns, including agent‑based and workflow‑driven architectures.
- Define model lifecycle standards, including versioning, auditability, traceability, and monitoring.

Analytics & Semantic Layer Architecture

- Led enterprise semantic layer design standards in Microsoft Fabric and Power BI, including measures, calculated fields, and KPI structures.
- Ensure KPI logic and metric definitions are consistently implemented across analytics assets.
- Establish architectural patterns supporting regulatory reporting, operational performance analytics, and executive decision intelligence.
- Provide architectural guidance for predictive analytics and advanced modeling initiatives.

Data Governance,



Quality & Compliance Architecture

- Led implementation patterns for enterprise data governance, including:
- Metadata management and classification (Microsoft Purview)
- Role‑based access control (RBAC)
- Data lineage and traceability
- Data quality monitoring and validation
- Ensure datasets supporting regulatory reporting, executive KPIs, and AI decisioning meet audit and compliance requirements.
- Identify systemic data quality or governance risks and drive architectural remediation strategies.

Platform Oversight & Delivery Alignment

- Provide architectural oversight during sprint planning and delivery execution in collaboration with delivery leadership.
- Guide resolution of systemic pipeline, data, or platform performance issues from an architectural perspective.
- Ensure approved architectural designs are implemented correctly and identify deviations early.
- Contribute to architecture reviews, design documentation, and technical standards.

Collaboration & Continuous Architecture Evolution

- Partner with analytics, data science, engineering, and business teams to translate requirements into scalable architectural solutions.
- Drive continuous improvement of data and AI architecture standards, patterns, and tooling.
- Stay current with emerging practices in data architecture, AI platforms, and MLOps.
- Maintain transparent, reusable architectural documentation to support governance, audit readiness, and knowledge sharing

For more information about this position, and to apply, please visit our website:

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Apply on Kit Job: kitjob.ca/job/2fs8wd

📌 Senior Data and AI Architect (Guelph)
🏢 Ontario One Call
📍 Guelph