Ontario One Call (OOC) is a Public Safety Administrative Authority; protecting Ontario by enabling safe digging. At OOC, public safety is at the heart of everything we do.
Since 2012, in Ontario, it's the law that any party planning to dig must contact OOC before they dig. OOC connects people planning to dig with the owners of underground pipes, cables, and other infrastructure to help prevent costly damages, service disruptions, and safety hazards. We also regulate an efficient locate system, foster industry wide collaboration, and promote safe, timely excavation across Ontario.
OOC is governed by a diverse Board of Directors, with experienced leaders representing underground infrastructure owners, excavators, ministry appointees and others dedicated to protecting Ontarians. Together, we work to shape a safer Ontario through collaboration, regulation, and education.
Safe Excavation starts with us.
Ontario One Call offers dynamic career opportunities in various areas such as operational services, compliance, regulatory affairs, communications, education, IT, finance and HR. When you join our team, you become an integral part of our mission-driven organization, dedicated to making Ontario safer, one dig at a time.
Caring…We invest in the success and safety for our team, communities and the environment.
Integrity...We are dedicated, honourable and honest.
Collaborative...We foster partnerships and work together to build a safer Ontario.
Inclusive...We are a leader in inclusivity and cultivate a foundation of respect and support within our industry.
Innovative...We strive for excellence with a willingness to learn, adapt and innovate.
Do you have what it takes to join our team?
The Senior 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.
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Data Platform Architecture & Design
- 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.
- AI & Machine Learning Architecture
- 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.
- Establish architectural guardrails for human‑in‑the‑loop controls and model retraining for medium‑ and high‑impact AI systems.
- 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.
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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 clear, reusable architectural documentation to support governance, audit readiness, and knowledge sharing
- Demonstrated experience designing, reviewing, and governing enterprise‑scale AI/ML systems, including LLM‑based architectures and retrieval‑augmented generation (RAG) patterns.
- Strong understanding of LLM behavior, non‑deterministic systems, and AI failure modes, sufficient to assess risk, architecture quality, and suitability for regulated environments.
- Experience defining architectural standards for MLOps / LLMOps, including model lifecycle management, evaluation approaches, and operational governance.
- Experience establishing architectural patterns for CI/CD pipelines supporting data and AI platforms, in collaboration with engineering and platform teams.
- Strong technical proficiency sufficient to evaluate, guide, and review engineering implementations involving Python‑based systems, APIs, containerized workloads, and cloud‑native architectures.
- Experience defining architectural patterns for AI observability, monitoring, and evaluation, including traceability, logging, and performance assessment.
- Strong background in AI security, identity, and access control architecture, including OAuth2, OIDC, SAML, and OWASP‑aligned practices.
- Experience acting as a senior technical authority in regulated, academic, or public‑sector environments, providing design guidance, architectural review, and risk‑aware oversight.
- Bachelor’s degree in Artificial Intelligence, Computer Science, Data Engineering, Information Systems, Software Engineering, or a related field (Masters Preferred); or a relevant discipline or combination of post-secondary education and experience.
- Minimum of 8 years of experience in data, analytics, or AI engineering roles, with demonstrated progression into enterprise architecture or technical design authority responsibilities.
- Formal training or certification in one or more of the following areas is an asset:
- Enterprise Architecture (e.g., TOGAF, cloud architecture frameworks)
- Data Architecture or Analytics Architecture
- AI governance, responsible AI, or model risk management
- Cloud platforms (e.g., Microsoft Azure architecture fundamentals)
- Starting salary of $130,000 - $150,000/annum dependent on qualifications and experience, with room to grow
- A comprehensive company paid benefit plan through Desjardins Life (at 3 months of service)
- CAAT DBPlus Pension Plan with Contribution Choice and Company Match (at 3 months of service)
- 3 weeks paid vacation
- 10 personal emergency days per year
- Highly engaged workforce and excellent workplace culture
- Diverse and inclusive environment
- Collaborative team
- New, clean and bright facility
- Bonus Potential
Imagine a workplace where everyone feels valued and respected. At Ontario One Call, we are committed to making this a reality through our Inclusion, Diversity, Equity & Accessibility (IDEA) initiatives, policy and committee. To achieve this, OOC strives to create a supportive work environment and a culture that welcomes diversity and uniqueness and encourages equitable opportunities for employees. Every individual person deserves respect, dignity and a sense of belonging. We encourage applications from individuals of all backgrounds, including those who may be underrepresented in our industry.
The salary advertised is reflective of a portion of the full pay grade range and is targeted at experienced, knowledgeable and skilled candidates.
In accordance with the Human Rights Code and the Accessibility for Ontarians with Disabilities Act, Ontario One Call is pleased to offer accommodations for job applicants with disabilities, if you require accommodations, please advise by contacting us.
Application reviews are done by a human. We thank all applicants for their interest; however only those candidates selected for an interview will be contacted.
We are currently recruiting for this open vacancy.
