Ontario Transit Group - 8 Jobs
Toronto, ON
Posted today
Job Details:
Full-time
Management
Salary:
The Senior Data Engineer MS Fabric Administrator is the primary technical owner of OTG's Microsoft Fabric platform and Power BI ecosystem. This role covers end-to-end platform administration, data engineering (pipelines, notebooks, Spark, Dataflows), and advanced Power BI development all in support of one of Canada's largest transit infrastructure projects, the Ontario Line.
The ideal candidate combines deep hands-on Fabric experience with strong Power BI skills and a genuine interest in driving AI-augmented workflows across the team. They are self-directed, documentation-focused, and comfortable operating in a fast-paced, cross-functional environment.
Key Responsibilities:
MS Fabric Administration & Data Engineering
- Administer the Fabric tenant: workspaces, capacity, security, governance, and tenant settings.
- Design and maintain Lakehouse architecture using the Bronze / Silver / Gold medallion storage pattern.
- Build and maintain data pipelines for ingestion, transformation, and orchestration across Fabric.
- Develop Python and PySpark notebooks for data processing and automation.
- Configure and manage Dataflows Gen2 using M Code and Power Query transformations.
- Implement API connections, User Data Functions, and Spark Jobs for custom data access.
Power BI Development
- Design and maintain advanced semantic models using DAX, parameters, and TMDL.
- Build polished, user-friendly reports applying UI/UX best practices and accessibility standards.
- Manage deployment pipelines, dataset lineage, and workspace governance across the tenant.
- Maintain model documentation and support self-service analytics across project teams.
AI Integration & Enablement
- Lead adoption of Fabric Copilot, Data Agents, and AI Functions in notebooks.
- Integrate AI tooling with the Fabric platform via MCP Servers (Power BI MCP, Fabric MCP).
- Champion the use of Claude Cowork and Cursor for AI-assisted development and automation.
- Document patterns and support team upskilling on AI-augmented workflows.
Qualifications:
- Bachelor's in Computer Science, Data Engineering, Information Systems, or a related field.
- Master's degree or post-grad specialization in Data Engineering / Cloud Computing is an asset.
- Microsoft Fabric Analytics Engineer Associate (DP-600) certified or actively in progress.
- 46 years of experience in data engineering, BI development, or a related function.
- Demonstrated hands-on experience administering Microsoft Fabric or an equivalent platform (Azure Synapse, Databricks).
- Proven track record delivering production-grade data pipelines and Power BI semantic models.
- Experience in large infrastructure, construction, or transit project environments is an asset.
- PL-300 (Power BI Data Analyst), DP-203 (Azure Data Engineer), or other MS certifications would be an asset.
- Strong analytical mindset with the ability to architect scalable, maintainable data solutions.
- Clear communicator able to translate complex technical concepts for non-technical stakeholders.
- Comfortable with DevOps and CI/CD practices for data (git-based TMDL deployments).
- Team leadership or mentoring experience is an asset.
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Frequently Asked Questions
This position is based in Toronto, ON.
This is a full-time position.
The role administers the Fabric tenant, designs lakehouse architecture, builds data pipelines, develops Python and PySpark notebooks, configures Dataflows Gen2, and implements API connections and Spark Jobs for data access.
You will work with Microsoft Fabric, Power BI, Python, PySpark, Dataflows Gen2, M Code, Power Query, and AI tooling like Fabric Copilot and MCP servers.
A Bachelor's in Computer Science or related field is required, with certifications like DP-600 as assets; 4–6 years of data engineering/BI experience is stated; hands-on Fabric or equivalent platform experience is required.
The role leads AI adoption with Fabric Copilot, Data Agents, and AI Functions, integrates AI tooling, and documents patterns to upskill the team on AI-augmented workflows.
