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Intermediate Data Engineer

  • Toronto, ON
  • On-site
  • Posted Sep 23, 2026
  • 1 position

$55,500–$120,000 / year

Opens an external site

Employment type
Full-time
Experience level
Mid-level · 2+ years
Apply by
Oct 12, 2026
Posting language
English
Working hours
40 hours per week

Job summary

The Data Engineer designs, builds, and maintains scalable data pipelines and integration solutions using cloud-based technologies. They collaborate with cross-functional teams to implement data models, ensure data quality, and support AI-enabled data products.

Job details

Application Deadline: 10/11/2026 Address: 4100 Gordon Baker Road Job Family Group: Technology Position Summary The Data Engineer is responsible for designing, building, and supporting scalable data solutions that enable analytics, reporting, regulatory, and operational business processes. Working as part of the Data Engineering team, the successful candidate will develop and maintain data pipelines, data integration solutions, data models, and cloud-based data platforms. The role will participate in the implementation of modern data technologies including Microsoft Fabric, cloud data platforms, data warehousing, and AI-enabled data solutions. The candidate will work closely with business stakeholders, data analysts, architects, and technology teams to deliver reliable, secure, and high-quality data products. Key Responsibilities Design, develop, test, and maintain batch and real-time data pipelines. Build and support ETL/ELT solutions using modern cloud-based technologies. Develop and optimize data ingestion, transformation, and consumption layers. Support data integration across enterprise platforms and source systems. Implement data quality, reconciliation, and validation controls. Assist with production support activities, root cause analysis, and issue resolution. Participate in migration and modernization initiatives involving Microsoft Fabric, cloud data platforms, and enterprise data warehouses. Develop reusable frameworks, automation utilities, and monitoring capabilities that improve operational efficiency. Collaborate with architects and senior engineers on data modelling, platform design, and solution implementation. Contribute to CI/CD implementation, automated testing, and DevOps practices. Work with governance and security teams to ensure compliance with enterprise data management standards. Participate in Agile ceremonies, technical design discussions, and estimation activities. Create technical documentation and support knowledge transfer activities. Microsoft Fabric & AI Responsibilities Design and develop data solutions using Microsoft Fabric including Data Factory, Lakehouse, Data Warehouse, Notebooks, and Real-Time Intelligence capabilities. Develop and optimize ELT pipelines within Microsoft Fabric. Implement Medallion Architecture patterns (Bronze, Silver, Gold) for enterprise data products. Build data models and curated datasets to support analytics and reporting workloads. Collaborate with AI and analytics teams to prepare data for machine learning and generative AI use cases. Develop AI-assisted operational solutions using Microsoft Copilot, Fabric AI capabilities, and intelligent automation frameworks. Support implementation of metadata management, lineage, and data observability capabilities. Participate in pilot initiatives involving AI-driven data quality monitoring, impact assessment, operational intelligence, and self-healing data pipelines. Required Skills Data Engineering SQL Python Data Warehousing Data Modelling ETL/ELT Development Data Integration Cloud Data Platforms Performance Optimization Data Quality Management Source-to-Target Mapping Microsoft Fabric Microsoft Fabric Fabric Data Factory Fabric Lakehouse Fabric Data Warehouse Fabric Notebooks OneLake Medallion Architecture Spark Fundamentals AI & Automation Generative AI Concepts AI-Assisted Development Tools Microsoft Copilot Prompt Engineering Fundamentals Data Preparation for Machine Learning Intelligent Process Automation Metadata and Data Lineage Concepts Salary: $55,500.00 - $120,000.00 Pay Type: Salaried The above represents BMO Financial Group’s pay range and type. Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position. BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards About Us At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world. As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset. To find out more visit us at https://jobs.bmo.com/ca/en. BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter. Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

What you’ll do

The Data Engineer designs, builds, and maintains scalable data pipelines and integration solutions using cloud-based technologies. They collaborate with cross-functional teams to implement data models, ensure data quality, and support AI-enabled data products.

Requirements

Candidates must possess strong skills in SQL, Python, and modern data engineering practices including ETL/ELT and cloud platforms. Experience with Microsoft Fabric, data modeling, and AI-assisted development tools is required for this role.

Benefits

• Health insurance • Tuition reimbursement • Accident insurance • Life insurance • Retirement savings plans • Performance-based incentives • Discretionary bonuses

Listed skills

  • SQL · Preferred
  • prompt engineering · Preferred
  • Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

  • Data Engineering
  • SQL
  • Python
  • Data Warehousing
  • Data Modelling
  • ETL/ELT
  • Data Integration
  • Cloud Data Platforms
  • Microsoft Fabric
  • Fabric Data Factory
  • Fabric Lakehouse
  • Spark
  • Generative AI
  • Prompt Engineering
  • Data Quality Management
  • Metadata Management
  • SQL (Programming Language)
  • Extract Transform Load (ETL)
  • Knowledge Transfer
  • Technical Documentation
  • Root Cause Analysis
  • Business Process
  • Data Modeling
  • Agile Methodology
  • Management
  • Governance
  • Milestones (Project Management)
  • Pipelines
  • Machine Learning
  • Data Pipelines
  • DevOps
  • Generative Artificial Intelligence
  • Artificial Intelligence
  • Data Quality
  • CI/CD
  • Coaching
  • Python (Programming Language)
  • Data Management
  • Test Automation
  • Azure Data Factory
  • Observability
  • Scalability
  • Automation
  • Economic Growth
  • Programming Tools
  • Operational Efficiency
  • Data Preprocessing
  • Reconciliation
  • Textiles
  • Operational Intelligence

Job areas

  • Technology
  • Data & Analytics
  • Software
  • Finance & Accounting
  • Engineering
  • Data Engineer
  • Generative Artificial Intelligence Engineer
  • Software Developers
  • Computer and Information Research Scientists