Senior Data Integration Developer, Fabric
Confirmed on the employer's own hiring board on Nov 6, 2026. First seen by Alion on Nov 2, 2026. KPMG Canada scores B on the Alion truth index.
At KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges. Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage. Join a firm where your career can make a difference.
The SeniorData Integration Developer (Fabric) designs, builds,and supports secure, scalable data integration solutions for KPMG Canada’sinternal clients through the Enterprise Analytics Centre of Excellence (CoE). Therole helpsestablishand operationalize Microsoft Fabric within a hybrid analytics ecosystem that includes the Enterprise Analytics Data Lake and Azure-native services.
The role combines hands-on data engineering with production reliability, platform governance, documentation, and stakeholder collaboration. Responsibilities span thedesign, deployment, monitoring, and optimization ofdata ingestion, transformation, orchestration, lakehouse, warehouse, and real-time solutions using Microsoft Fabric, OneLake, and related Azure services.
What you will do
Data engineering and modernization
- Design and implement end-to-end Fabric data engineering solutions for downstream reporting and analytics using Data Factory pipelines, Dataflows Gen2, notebooksand OneLake
- Build and maintainreliable batchand, where required, streamingdata pipelines using Fabric Data Factory, Spark/PySpark, Eventstreams, and Real-Time Intelligence capabilities
- Develop extract, transform, load (ETL) and extract, load, transform (ELT) processes to ingest data from on-premises, cloud, API, file, database, and event-based sources into governed Fabric data stores
- Implement medallion architecture patterns across Bronze, Silver, and Goldlayers, using Delta tables and reusable transformation frameworks
- Design and optimizeFabric OneLakesolutions, SQL endpoints, data models, and curated data products for downstream reporting and analytics
- Support migration and modernization of legacy, on-premises, Azure Data Factory, Synapse, or other Azure data workloads into Microsoft Fabric where appropriate
- Develop and optimizeSQL, Databricks (PySpark)andPython transformations to prepare, validate, and enrich data for analytics use cases
Production reliability and optimization
- Monitor capacity, pipelines, notebooks, refreshes, data quality, and workload performance.Diagnose failures and implement sustainable corrective actions
- Create operational runbooks,architecture diagrams, data flow documentation, support procedures, and technical standards for Fabric solutions
Security, governance, and delivery practices
- Apply source control, branching, automated testing, deployment pipelines, and release-management practices usingGit or equivalent tooling
- Implement and operatesecurity and governance controls, including workspace roles, least-privilege access, row-level security, sensitivity considerations, lineage, and Microsoft Purview integration
Collaboration and technical standards
- Collaborate with architects, analytics engineers, data analysts, business analysts, administrators, and business stakeholders to translate requirements into technical solutions that can be maintainedand supported in production
- Contribute technical judgment through design reviews, platform standards, reusable assets, proof-of-concept projects, and continuous improvement of the Enterprise Analytics operating model
What you bring to the role
- University degree or college diploma in computer science, computer engineering, data engineering, information systems, mathematics, or a relateddiscipline, or equivalent practical experience
- Four or more years of professional experience in data engineering, data integration, analytics engineering, business intelligence engineering, or a related field
- Hands-on experience with Microsoft Fabric and/or comparable Azure data technologies, including Azure Data Factory, Synapse Analytics, Azure Data LakeandDatabricks
- Experience designing and supporting scalable data integration solutions, including ETL/ELT pipelines, data orchestration, and enterprise data platforms
- Strong SQL skills and practical experience with data warehousing, lakehousearchitectures, dimensional modeling, and performance optimization
- Proficiencyin Python and PySparkfor data transformation, automation, and troubleshooting
- Experience working with Fabric components such as OneLake, Lakehouse, Warehouse, Data Factory, notebooks, and Delta tables
- Understanding ofmodern data architecture concepts, including Medallion architecture, data governance, metadata management, security, and lifecycle management
- Experience with Git-based source control, CI/CD practices, and deployment automation
- Ability to monitor, troubleshoot, and optimizeproduction data solutions while supporting operational reliability
- Experience collaborating with business and technical stakeholders to translate requirements into scalable analytics solutions
KPMG Ontario Region Pay Range Information
The expected base salary range for this position is $87,500 to $130,500 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.
Providing you with the support you need to be at your best
Our Values, The KPMG Way
Integrity, we do what is right | Excellence, we never stop learning and improving | Courage, we think and act boldly | Together, we respect each other and draw strength from our differences | For Better, we do what matters
KPMG in Canada is a proud equal opportunities employer and we are committed to creating a respectful, inclusive and barrier-free workplace that allows all of our people to reach their full potential. A diverse workforce is key to our success and we believe in bringing your whole self to work. We welcome all qualified candidates to apply and hope you will choose KPMG in Canada as your employer of choice.
Adjustments and accommodations throughout the recruitment process
At KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel. We aim to provide a positive experience and are prepared to offer adjustments or accommodations to help you perform at your best. Adjustments (informal requests), such as extra preparation time or the option for micro breaks during interviews, and accommodations (formal requests), such as accessible communication supports or technology aids, are tailored to individual needs and role requirements. You will have an opportunity to request an adjustment or accommodation at any point throughout the recruitment process. If you require support, please contact KPMG’s Employee Relations Service team by calling 1-888-466-4778.
AI Usage
We embrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. AI tools may help with organizing applications or surfacing relevant qualifications. However, no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals, who are equipped with training that empowers them to use these tools responsibly. AI technologies used in our recruitment process undergo detailed risk assessments, including security and privacy requirements, that align with KPMG’s Trusted AI framework.
We believe technology should empower human judgment, not replace it. It’s one of the many ways we’re delivering on our vision of being a technology-first, people-driven firm.
Data engineering and modernization
- Design and implement end-to-end Fabric data engineering solutions for downstream reporting and analytics using Data Factory pipelines, Dataflows Gen2, notebooksand OneLake
- Build and maintainreliable batchand, where required, streamingdata pipelines using Fabric Data Factory, Spark/PySpark, Eventstreams, and Real-Time Intelligence capabilities
- Develop extract, transform, load (ETL) and extract, load, transform (ELT) processes to ingest data from on-premises, cloud, API, file, database, and event-based sources into governed Fabric data stores
- Implement medallion architecture patterns across Bronze, Silver, and Goldlayers, using Delta tables and reusable transformation frameworks
- Design and optimizeFabric OneLakesolutions, SQL endpoints, data models, and curated data products for downstream reporting and analytics
- Support migration and modernization of legacy, on-premises, Azure Data Factory, Synapse, or other Azure data workloads into Microsoft Fabric where appropriate
- Develop and optimizeSQL, Databricks (PySpark)andPython transformations to prepare, validate, and enrich data for analytics use cases
Production reliability and optimization
- Monitor capacity, pipelines, notebooks, refreshes, data quality, and workload performance.Diagnose failures and implement sustainable corrective actions
- Create operational runbooks,architecture diagrams, data flow documentation, support procedures, and technical standards for Fabric solutions
Security, governance, and delivery practices
- Apply source control, branching, automated testing, deployment pipelines, and release-management practices usingGit or equivalent tooling
- Implement and operatesecurity and governance controls, including workspace roles, least-privilege access, row-level security, sensitivity considerations, lineage, and Microsoft Purview integration
Collaboration and technical standards
- Collaborate with architects, analytics engineers, data analysts, business analysts, administrators, and business stakeholders to translate requirements into technical solutions that can be maintainedand supported in production
- Contribute technical judgment through design reviews, platform standards, reusable assets, proof-of-concept projects, and continuous improvement of the Enterprise Analytics operating model
- University degree or college diploma in computer science, computer engineering, data engineering, information systems, mathematics, or a relateddiscipline, or equivalent practical experience
- Four or more years of professional experience in data engineering, data integration, analytics engineering, business intelligence engineering, or a related field
- Hands-on experience with Microsoft Fabric and/or comparable Azure data technologies, including Azure Data Factory, Synapse Analytics, Azure Data LakeandDatabricks
- Experience designing and supporting scalable data integration solutions, including ETL/ELT pipelines, data orchestration, and enterprise data platforms
- Strong SQL skills and practical experience with data warehousing, lakehousearchitectures, dimensional modeling, and performance optimization
- Proficiencyin Python and PySparkfor data transformation, automation, and troubleshooting
- Experience working with Fabric components such as OneLake, Lakehouse, Warehouse, Data Factory, notebooks, and Delta tables
- Understanding ofmodern data architecture concepts, including Medallion architecture, data governance, metadata management, security, and lifecycle management
- Experience with Git-based source control, CI/CD practices, and deployment automation
- Ability to monitor, troubleshoot, and optimizeproduction data solutions while supporting operational reliability
- Experience collaborating with business and technical stakeholders to translate requirements into scalable analytics solutions
KPMG Ontario Region Pay Range Information
The expected base salary range for this position is $87,500 to $130,500 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.
Providing you with the support you need to be at your best