Senior Data Engineer – Azure Data Factory & Databricks
About the role
Position Title: Data Engineer
Level: MP4 Number of Vacancies: 2 Contract Duration: 11 months (renewable) Hours of Work: 35 hours per week Location: 1908 Colonel Sam Drive, Oshawa – Hybrid, 3 days remote Resume Due Date: Monday, July 27, 2026, at 5:00 PM EST Hourly Rate: $90-$95+HST Site Security Clearance is a condition of employment.
We are seeking experienced Azure and Databricks Data Engineers with strong hands-on experience designing, building, developing, and supporting data pipelines end-to-end. This role requires candidates who have actively developed pipelines using Azure Data Factory, Azure Databricks, PySpark, Spark SQL, Python, and SQL. Candidates whose experience is primarily limited to using prebuilt frameworks, entering parameters into CSV files, or updating configuration files will not be the best fit.
The Data Engineer will be responsible for designing, building, and supporting data-driven applications that enable innovative and customer-focused digital experiences. The successful candidate will work as part of a cross-functional agile team to deliver reliable, scalable, secure, and high-performing data products. These products will support reporting, analytics, applications, innovation, and downstream enterprise data use. The Data Engineer will build and productionize modular, scalable ELT/ETL pipelines and data infrastructure using data from a wide range of enterprise sources. They will help create curated common data models, support data lakehouse and data warehouse solutions, and ensure data products are secure, accurate, well-documented, and optimized for performance.
The Data Engineer will be responsible for the following
Design, build, test, deploy, and support scalable data pipelines using Azure and Databricks technologies. Build modular and production-ready ELT/ETL pipelines using data from multiple enterprise sources. Develop data lakehouse and data warehouse solutions to support reporting, analytics, applications, and downstream systems. Work with Azure Data Factory, Azure Data Lake, Azure SQL Database, Azure Synapse Analytics, Azure Databricks, Microsoft Purview, and Power BI. Develop optimized and performant data pipelines using Python, PySpark, Spark SQL, and SQL. Ingest and process data from sources such as XML, CSV, JSON, REST APIs, databases, and other structured or semi-structured formats. Clean, transform, prepare, and optimize datasets for reporting, analytics, and application use. Implement data quality checks, lineage, metadata, and governance controls throughout the data integration lifecycle. Build curated common data models designed by Data Modelers in collaboration with Data Architects. Support dimensional data modelling and aggregation optimization for Business Intelligence and reporting teams. Troubleshoot ingestion, transformation, data accuracy, integrity, and pipeline performance issues. Work with infrastructure, cybersecurity, and senior data engineering teams to ensure data is secure in transit and at rest. Implement and manage role-based access controls for data products based on guidance from senior team members. Assist with the creation and maintenance of data catalogues and metadata for enterprise datasets. Document as-built pipelines, data flows, data products, and technical designs. Use source control and maintain a clean, reliable, and maintainable code base. Participate in peer code reviews. Write and execute automated unit tests and regression tests for data pipeline builds. Support user acceptance testing and system integration testing as required. Work with CI/CD and DevOps pipelines to support automated infrastructure, code deployment, release management, and version control. Monitor production data solutions and provide Tier 2 support for datasets produced by the team. Identify and implement process improvements, including automation, performance optimization, scalability improvements, and reduction of manual work. Collaborate with Business Analysts, Data Scientists, Senior Data Engineers, Data Analysts, Solution Architects, Data Architects, and Data Modelers. Work within an agile Scrum delivery model, including contributing to feature development, user stories, backlog refinement, and Kanban/Scrum activities.
Candidates must have
Completion of a four-year university degree in computer science, computer/software engineering, data engineering, data analysis, artificial intelligence, machine learning, or a related field. Hands-on experience as a Data Engineer designing and building data pipelines. Strong experience with Azure Data Factory. Strong experience with Azure Databricks. Experience with Azure Data Lake Storage, Synapse Analytics, and Azure SQL databases. Strong programming experience with Python, PySpark, Spark SQL, and SQL. Experience building pipelines for data lakehouses and data warehouses. Good understanding of data structures and data processing frameworks. Knowledge of data governance and data quality principles. Experience developing pipelines that process XML, CSV, JSON, REST API, database, or similar source data. Effective communication skills, including the ability to explain technical concepts to non-technical stakeholders.
Preference will be given to candidates who have
Built Azure Data Factory and Databricks pipelines from scratch. Designed and developed end-to-end data ingestion, transformation, and orchestration processes. Worked outside the financial services industry. Experience with lakehouse architecture, including bronze, silver, and gold data layers. Experience with metadata management, Microsoft Purview, data cataloguing, and lineage. Experience with CI/CD, DevOps, automated testing, and source control. Experience optimizing Spark jobs, SQL queries, and pipeline performance. Experience supporting production data pipelines and resolving operational issues.
Not the right fit? Search for Data Engineer jobs in Oakville, Ontario, Canada
About CPUS Engineering Staffing Solutions Inc.
CPUS Engineering Staffing Solutions Inc. (CPUS) is a privately-owned Canadian staffing agency formed exclusively to provide technical staffing solutions to the power industry. CPUS supplies the power industry with the best candidates in the market on an ‘as required basis’ to work on managed task projects at competitive rates, as well as recruit them on behalf of power industry clients. At CPUS, we aim to become the leading provider of staff to the power industry by giving the best available experts for project work while maintaining an improved rate structure, resulting in substantial savings for our clients.
CPUS Limited is a design and project management, procurement, and engineering services consultancy company, formed exclusively to support the Canadian power industry. CPUS Engineering works with CPUS Limited to provide engineering services consultancy.
CPUS Engineering is a Certified Canadian Aboriginal and Minority Supplier.
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Senior Data Engineer – Azure Data Factory & Databricks
About the role
Position Title: Data Engineer
Level: MP4 Number of Vacancies: 2 Contract Duration: 11 months (renewable) Hours of Work: 35 hours per week Location: 1908 Colonel Sam Drive, Oshawa – Hybrid, 3 days remote Resume Due Date: Monday, July 27, 2026, at 5:00 PM EST Hourly Rate: $90-$95+HST Site Security Clearance is a condition of employment.
We are seeking experienced Azure and Databricks Data Engineers with strong hands-on experience designing, building, developing, and supporting data pipelines end-to-end. This role requires candidates who have actively developed pipelines using Azure Data Factory, Azure Databricks, PySpark, Spark SQL, Python, and SQL. Candidates whose experience is primarily limited to using prebuilt frameworks, entering parameters into CSV files, or updating configuration files will not be the best fit.
The Data Engineer will be responsible for designing, building, and supporting data-driven applications that enable innovative and customer-focused digital experiences. The successful candidate will work as part of a cross-functional agile team to deliver reliable, scalable, secure, and high-performing data products. These products will support reporting, analytics, applications, innovation, and downstream enterprise data use. The Data Engineer will build and productionize modular, scalable ELT/ETL pipelines and data infrastructure using data from a wide range of enterprise sources. They will help create curated common data models, support data lakehouse and data warehouse solutions, and ensure data products are secure, accurate, well-documented, and optimized for performance.
The Data Engineer will be responsible for the following
Design, build, test, deploy, and support scalable data pipelines using Azure and Databricks technologies. Build modular and production-ready ELT/ETL pipelines using data from multiple enterprise sources. Develop data lakehouse and data warehouse solutions to support reporting, analytics, applications, and downstream systems. Work with Azure Data Factory, Azure Data Lake, Azure SQL Database, Azure Synapse Analytics, Azure Databricks, Microsoft Purview, and Power BI. Develop optimized and performant data pipelines using Python, PySpark, Spark SQL, and SQL. Ingest and process data from sources such as XML, CSV, JSON, REST APIs, databases, and other structured or semi-structured formats. Clean, transform, prepare, and optimize datasets for reporting, analytics, and application use. Implement data quality checks, lineage, metadata, and governance controls throughout the data integration lifecycle. Build curated common data models designed by Data Modelers in collaboration with Data Architects. Support dimensional data modelling and aggregation optimization for Business Intelligence and reporting teams. Troubleshoot ingestion, transformation, data accuracy, integrity, and pipeline performance issues. Work with infrastructure, cybersecurity, and senior data engineering teams to ensure data is secure in transit and at rest. Implement and manage role-based access controls for data products based on guidance from senior team members. Assist with the creation and maintenance of data catalogues and metadata for enterprise datasets. Document as-built pipelines, data flows, data products, and technical designs. Use source control and maintain a clean, reliable, and maintainable code base. Participate in peer code reviews. Write and execute automated unit tests and regression tests for data pipeline builds. Support user acceptance testing and system integration testing as required. Work with CI/CD and DevOps pipelines to support automated infrastructure, code deployment, release management, and version control. Monitor production data solutions and provide Tier 2 support for datasets produced by the team. Identify and implement process improvements, including automation, performance optimization, scalability improvements, and reduction of manual work. Collaborate with Business Analysts, Data Scientists, Senior Data Engineers, Data Analysts, Solution Architects, Data Architects, and Data Modelers. Work within an agile Scrum delivery model, including contributing to feature development, user stories, backlog refinement, and Kanban/Scrum activities.
Candidates must have
Completion of a four-year university degree in computer science, computer/software engineering, data engineering, data analysis, artificial intelligence, machine learning, or a related field. Hands-on experience as a Data Engineer designing and building data pipelines. Strong experience with Azure Data Factory. Strong experience with Azure Databricks. Experience with Azure Data Lake Storage, Synapse Analytics, and Azure SQL databases. Strong programming experience with Python, PySpark, Spark SQL, and SQL. Experience building pipelines for data lakehouses and data warehouses. Good understanding of data structures and data processing frameworks. Knowledge of data governance and data quality principles. Experience developing pipelines that process XML, CSV, JSON, REST API, database, or similar source data. Effective communication skills, including the ability to explain technical concepts to non-technical stakeholders.
Preference will be given to candidates who have
Built Azure Data Factory and Databricks pipelines from scratch. Designed and developed end-to-end data ingestion, transformation, and orchestration processes. Worked outside the financial services industry. Experience with lakehouse architecture, including bronze, silver, and gold data layers. Experience with metadata management, Microsoft Purview, data cataloguing, and lineage. Experience with CI/CD, DevOps, automated testing, and source control. Experience optimizing Spark jobs, SQL queries, and pipeline performance. Experience supporting production data pipelines and resolving operational issues.
Not the right fit? Search for Data Engineer jobs in Oakville, Ontario, Canada
About CPUS Engineering Staffing Solutions Inc.
CPUS Engineering Staffing Solutions Inc. (CPUS) is a privately-owned Canadian staffing agency formed exclusively to provide technical staffing solutions to the power industry. CPUS supplies the power industry with the best candidates in the market on an ‘as required basis’ to work on managed task projects at competitive rates, as well as recruit them on behalf of power industry clients. At CPUS, we aim to become the leading provider of staff to the power industry by giving the best available experts for project work while maintaining an improved rate structure, resulting in substantial savings for our clients.
CPUS Limited is a design and project management, procurement, and engineering services consultancy company, formed exclusively to support the Canadian power industry. CPUS Engineering works with CPUS Limited to provide engineering services consultancy.
CPUS Engineering is a Certified Canadian Aboriginal and Minority Supplier.