GIS & AI Analytics Engineer

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.

Job Description

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.

1. 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.

1. 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.

1. 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.

Qualifications

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

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 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.