GIS & AI Analytics Engineer

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 nonGIS domains. The role designs and delivers AIready 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 AInatively 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 BronzeSilverGold 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) AINative 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. 

Qualifications :

• Bachelors 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 (PL300) 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 BronzeSilverGold 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 
• BronzeSilverGold 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 

Additional Information :

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 youre ready to be part of our dynamic team in one of the worlds most diverse cities dont wait any longerapply now!

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

Remote Work :

No

Employment Type :

Full-time