Ferrovial Construction Canada Inc. and VINCI Construction Grands Projects are undertaking the design, build, and finance the Ontario Line Southern Civil, Stations, and Tunnel (South Civil) package.

As Ontario Transit Group, we are now mobilizing our design and construction crews, with major works. The South Civil contract is anticipated to be completed in 2030.

The project will strengthen Ontario’s economy by supporting an estimated 1,500 jobs at the peak of construction.

What is the project?

• A six-kilometer tunnel and associated tunnelling works from Exhibition to Don Yard portal (west of the Don River).
• Stations:
  • One above-ground station to be integrated with the existing GO Transit Exhibition Station.
  • Two underground stations to be integrated with the existing TTC Osgoode and Queen subway stations.
  • Four new underground stations (King/Bathurst, Queen/Spadina, Moss Park, Corktown).

The benefits to Ontario!

Faster, more frequent, and reliable access to rapid transit with more than 227,500 people will live within a 10-minute walk of an Ontario Line station.

• Improve the quality of life for commuters by reducing daily travel time.
• Reduce crowding on the existing Line 1 (Yonge-University) subway.
• Up to 57,000 more jobs accessible by transit (in 45 minutes or less) for Toronto residents.
• Economic and community growth along the future transit line and thousands of job opportunities annually during construction.
• Reduction in traffic congestion, greenhouse gases, and fuel consumption by providing an alternative transportation option.

The GIS & AI Analytics Engineer owns 100% of all GIS datasets, spatial strategy, and semantics, while also supporting enterprise-wide analytics across both GIS and non‑GIS domains. The role designs and delivers AI‑ready data products using Microsoft Fabric and Power BI embedding ontologies and knowledge graphs to ensure consistent meaning, relationships, and reuse across data, reports, and AI experiences.  

Working AI‑natively, this role uses AI as a default accelerator for analytics, automation, and documentation, continuously identifying opportunities to eliminate manual effort and improve how users interact with data. 

      1) Enterprise GIS Ownership, Semantics & Strategy 

         Single accountable owner for GIS data, meaning, and spatial semantics. 

• Own 100% of all GIS datasets, including:  
• authoritative sources, schemas, refresh cadence, quality thresholds 
• spatial accuracy, lineage, versioning, and lifecycle management 
• Define and evolve the GIS strategy and roadmap, aligned with analytics, AI, and business outcomes.

        Design and maintain a spatial ontology:  

• standardized definitions of assets, locations, zones, constraints, and relationships 
• clear differentiation between raw geometry, analytical entities, and business concepts 

        Contribute GIS entities into a project-wide knowledge graph connecting:  

• spatial assets ↔ cost ↔ schedule ↔ risks ↔ progress ↔ documents 
• Act as the semantic authority for all spatial concepts to ensure consistent interpretation across reports, AI agents, and users. 

    2) Data Platform Engineering 

• Builds analytics- and AI-ready data products, spatial and non-spatial. 
• Design and implement Bronze–Silver–Gold architecture in Microsoft Fabric:  
• Embed ontology-aligned IDs and relationships across datasets to support:  
• consistent joins between GIS and operational data 
• downstream knowledge graph generation 

            Ensure all curated datasets are:  

• analytics-ready (Power BI) 
• AI-consumable (Copilot, semantic search, reasoning) 
• Implement automated validation, reconciliation, and observability across layers. 

    3) Analytics, Visualization & Semantic Modeling (Power BI) 

• Transforms data into trusted insights with semantic clarity. 
• Build and manage Power BI semantic models grounded in:  
• dimensional best practices 
• ontology-backed definitions of measures, entities, and hierarchies 

         Deliver dashboards and analytical products for:  

• GIS datasets 
• non-GIS enterprise datasets 
• integrated spatial + operational insights 

        Enable self-service analytics using:  

• certified datasets 
• semantic layer reuse 
• consistent KPI definitions across reports 
• Ensure reports, metrics, and AI summaries all reference the same semantic truth. 

   4) AI‑Native Automation, Knowledge Graphs & Continuous Improvement 

• AI-first mindset; every workflow is a candidate for automation. 
• Work natively with AI in all aspects of delivery:  
• data modeling, pipeline creation, DAX/SQL/Python generation 
• documentation, summarization, anomaly detection 

         Build and evolve knowledge graphs that connect:  

• GIS entities 
• datasets, reports, KPIs 
• documents, decisions, and risks 

       Use ontologies + knowledge graphs to enable:  

• semantic search (“show risks affecting this zone”) 
• AI-generated explanations and summaries 
• intelligent navigation across data and reports 
• Observe users, tasks, and recurring requests to:  
• identify inefficiencies 
• replace manual processes with AI-assisted or automated solutions 
• Ensure AI usage is secure, governed, and aligned with enterprise policies. 

• Bachelor’s degree or diploma in GIS, Geomatics, Geography, Data Analytics, Computer Science, Engineering, or a related field  
• Equivalent practical experience with a strong analytics/GIS portfolio considered in lieu of formal education 
• Min of 3 years’ experience working with: Esri or GIS-related certification (ArcGIS Pro / ArcGIS Online), Power BI Data Analyst Associate (PL‑300) or equivalent analytics certification, Microsoft Fabric, Azure Fundamentals, or data engineering certifications are an asset, GIS datasets and spatial workflows , Data analytics or data engineering in BI platforms, Hands-on experience with Power BI and analytics data modeling , Experience integrating data from multiple sources (GIS, enterprise systems, files, APIs)  
• Exposure to AI-assisted analytics and automation workflows 
• Working knowledge of Microsoft Fabric concepts (Lakehouse, pipelines, dataflows, notebooks)  
• Understanding of Bronze–Silver–Gold data architecture principles  
• Familiarity with ontologies, semantic models, or knowledge graphs (conceptual or applied)  
• Strong ownership mindset; able to own datasets end-to-end and act as the single source of truth  
• Ability to translate business questions into scalable data and analytics solutions  
• Analytical thinking with attention to data quality, consistency, and meaning  
• Clear communicator, able to work with technical and non-technical stakeholders  
• Organized, adaptable, and able to operate independently in a fast-moving environment 
• Comfort using AI as a daily productivity tool (analysis, automation, documentation, prototyping)  
• Ability to identify inefficiencies and proactively propose automation and AI-driven improvements 

GIS & Spatial Technologies 

• ArcGIS Pro / ArcGIS Online / ArcGIS Enterprise or QGIS 
• Spatial data formats (feature services, geodatabases, shapefiles, raster) 
• Coordinate systems, projections, topology, and spatial QA/QC 
• Spatial analysis and GIS data lifecycle management 

Data & Analytics Platforms 

• Microsoft Fabric: Lakehouse, Warehouse, Dataflows, Pipelines, Notebooks 
• Power BI: semantic models, DAX fundamentals, report development, performance optimization 
• Bronze–Silver–Gold data architecture and analytics-ready data modeling 
• SQL for data transformation and analysis 

Automation & Integration 

• Data ingestion from APIs, SharePoint, files, enterprise systems 
• Power Automate or Fabric pipelines for automation and orchestration 
• Python for data processing and analytics (pandas; geopandas an asset) 

AI, Semantics & Knowledge Representation 

• AI-assisted analytics workflows (Copilot, prompt-driven analysis, automation support) 
• Semantic modeling concepts and KPI standardization 
• Knowledge graphs and ontologies (entity definitions, relationships, reusable semantics) 
• Semantic search and AI-consumable data structures 

Data Governance & Quality 

• Data validation, reconciliation, and monitoring practices 
• Dataset certification, access control, and documentation 
• Understanding of secure and governed AI usage in enterprise environments 

We Offer: 

• Competitive Salary
• Comprehensive Benefits Package:
  • Disability Insurance
  • Dental Insurance
  • Extended medical insurance
  • (Optional) RRSP matching
  • Discretionary Bonus

Why OTG?

Welcome to Ontario Transit Group (OTG), located in the heart of Downtown Toronto, where diversity and passion collide. As we work on the groundbreaking Ontario Line project, we prioritize fostering a positive culture. Join us and be part of a team that celebrates our employees, organizes family events, and promotes health and wellness initiatives. Our commitment to personal and professional growth means annual performance reviews, salary increases, comprehensive health benefits, generous RRSP matching, industry education support, and career development opportunities.

At OTG, we embrace diversity, recognizing that it strengthens us as a team and as a company. We are an equal-opportunity employer, encouraging applications from all interested candidates. We value Indigenous people, racialized people, neurodivergent people, people with disabilities, and individuals from gender and sexually diverse communities with intersectional identities. Reasonable accommodations are available upon request for people with disabilities. If you're ready to be part of our dynamic team in one of the world's most diverse cities, don't wait any longer—apply now!

While we appreciate your interest, only selected candidates will be contacted for interviews. Please note that we do not accept agency submissions.