Microsoft Fabric data Engineer (Toronto)

Microsoft Fabric data Engineer (Toronto)

04 Sep
|
Blackbuck Insights
|
Toronto

04 Sep

Blackbuck Insights

Toronto

Job Information

- Industry IT Services
- Date Opened 08/17/2026
- Job Type Full time
- Work Experience 5-10 years
- City Toronto
- State/Province Ontario
- Country Canada
- Zip/Postal Code M4C

About Us

BBI is a global data engineering consulting firm that empowers clients to effectively scale and modernize. We combine engineering fundamentals and innovative tools to execute business-critical, end-to-end projects on-time and on-budget. We offer expert services across Data Integration, Data Modernization, Data Migration, Data Architecture, Platform Support, and Application Services. Our goal is to provide business value in the most effective way for our clients so clients can focus on growth.

MS fabric Data Engineer Role

- Overview of The Role

The Data Engineer is responsible for designing, building, and supporting scalable, secure, and high‑performance analytics solutions on the Microsoft Fabric platform. This role combines strong technical depth with business acumen to translate evolving business needs into trusted data products. The individual will play a key role in shaping and executing our clients modern BI and analytics strategy.
- How You Will Make Contributions That Matter:
- Partner closely with stakeholders to translate business requirements into Fabric-based data models, pipelines, and analytical solutions
- Contribute to the end-to-end design and evolution of a scalable enterprise analytics architecture using Microsoft Fabric
- Collaborate with Business SMEs and technical teams (Infrastructure, Security, Dynamics, external) to design and deliver sustainable, governed analytics solutions
- Assist with preparation and facilitation of design workshops with documented outcomes (requirements, design, data models)
- Ensure solutions are scalable, secure, cost-effective, and aligned with data & ai strategy
- Design and develop high-performance data engineering components capable of processing large volumes of structured and semi-structured data
- Build reusable, enterprise-grade data models (Lakehouse and semantic models) aligned with architectural standards and best practices
- Contribute to administration,



governance, and operational health of the Microsoft Fabric platform
- Define and execute test strategies, including data validation, performance tuning, and data profiling
- Monitor Fabric pipelines, data refreshes, and workloads, proactively troubleshoot and resolve issues
- Own incident resolution and day-to-day sustainment of Fabric analytics solutions
- tilize Microsoft Analytics tools for seamless integration and efficient user interface development to enhance overall user experience
- Optimize SQL, Spark, and DAX queries for performance and scalability
- Mentor analytics, functional and business teams on Microsoft Fabric capabilities, patterns, and best practices Contributes to work effort estimation for new and enhanced project opportunities

- Supervision
- Acts as an individual contributor and operates independently while ensuring alignment with enterprise BI and analytics strategy
- Can oversee project and support activities such as troubleshooting, enhancements, capacity planning, upgrades, and migrations Communicates clearly and collaborates effectively with cross-functional and geographically distributed teams

- Qualifications
- Bachelor’s degree in information systems, Computer Science, Software Engineering, or equivalent experience
- 5+ years of hands-on experience delivering enterprise analytics and data engineering solutions on Microsoft platforms
- Strong experience engineering solutions on Microsoft Fabric and up-to-date Azure analytics services, with understanding and working knowledge of other industry-standard analytics and data engineering tools.
- Microsoft Azure / Fabric certifications

- Strong foundation in

- Data ingestion and integration

- Data transformation and orchestration




- Data storage, data lakes, and lakehouse architecture
- Data warehousing and dimensional modeling
- Experience with CI/CD, DevOps, and source control (Azure DevOps, GitHub)
- Understanding of administration, security, and governance for Microsoft analytics platforms
- Experience with enterprise delivery methodologies (Agile/ Waterfall) and estimation practices
- Robust understanding of Optimization techniques to improve ingestion process
- Experience in building real time solutions end to end
- Experience in ingesting data from SaaS, on-prem, PaaS, SharePoint and different file formats
- Understanding of advanced AI technologies like ML, Agentic AI.
- Strong written and verbal communication skills, especially for technical design documentation
- Ability to operate effectively across complex, interdependent workstreams, teams, and geographies

Up-to-date knowledge of industry trends and best practices in data engineering and analytics
- Technical qualifications
- Strong hands-on experience as a Data Engineer on Microsoft Fabric and Azure platforms, including:
- Fabric Lakehouse/Warehouse/Event House/ Materialized Lake view
- Fabric Ingestion (Data Factory, Pipelines, Dataflow Gen1, Dataflow Gen2, Copy Job, Notebooks, EventStream, Spark Job Definition, Spark structure streaming)

- Fabric Orchestration (Apache Airflow)
- Data Engineering Languages (Py-Spark/Spark SQL /KQL)
- Experience with Azure analytics services, including:

- Azure Data Factory

- Azure Synapse Analytics

- Azure Data Lake Storage

- Azure Databricks (where applicable)
- Development using Python and Spark notebooks
- Understanding of data modeling skills, including dimensional modeling (Kimball / star schema)
- Advanced SQL skills for analytical workloads
- Good understanding of Power BI
- Workspace, security, and capacity management
- Solid understanding of DevOps / GitHub for version control and CI/CD
- Practical understanding of Microsoft Fabric governance, security (One Lake Security, SQL security), and workload management

📌 Microsoft Fabric data Engineer (Toronto)
🏢 Blackbuck Insights
📍 Toronto

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