Databricks Data Engineer Jobs in Ontario (NOW HIRING)

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.

Are you a talented leader with a proven track record for motivating teams and delivering exceptional client service?

Our team is looking for a Data Engineer with extensive hands-on expertise in Databricks and strong consulting capability. This role will support and lead modernization initiatives from legacy/on-prem data platforms to scalable, secure, and cost-optimized Lakehouse architectures using Databricks and similar technologies.

• Partner with clients to understand business goals, gather requirements, and translate them into actionable technical designs and delivery plans.
• Work with the engagement team to translate business and analytics requirements into a data strategy for the engagement including ETL/ELT, data model, and staging data for analysis.
• Contribute to end-to-end solution architecture for repeatable, cost-optimized implementations (including non-functional requirements and operational readiness).
• Lead delivery of modern data platforms on Databricks (ETL/ELT pipelines, workload migrations, governance enablement).
• Implement Delta Lake / Lakehouse patterns including medallion architecture, CDC, incremental processing, and data quality controls.
• Develop data pipelines to support streaming, incremental, batch data, etc.
• Design and implement scalable batch and streaming pipelines using Spark and modern orchestration patterns.
• Apply CI/CD and engineering best practices (version control, automated deployment, testing, and release management) to data engineering workflows.
• Establish and operationalize governance using Unity Catalog, including access controls, lineage, and security frameworks.
• Support testing and production releases, including troubleshooting, performance tuning, and stabilization.
• Proactively contributes to the creation of presentation materials relating to data activities for stakeholder discussions.

• University degree in computer engineering, mathematics, data science or related disciplines
• 4+ years of professional experience in a related field like Data Engineering, Business Intelligence, or related field with a track record of manipulating, processing, and extracting value from large datasets.
• 2+ years of hands-on experience with Databricks, including advanced features (Delta Lake, Unity Catalog) with Databricks or cloud certifications with 1-2 years of experience leading workstreams / client-facing delivery.
• Strong proficiency in SQL and solid understanding of modern data modeling principles, dimensional modeling, and data warehousing concepts.
• Proficiency in Python (or similar scripting languages) for data processing, automation, and analytical workflows
• Strong experience working in teams to perform ETL (extract, transform and load) of data from a variety of databases from SQL, NoSQL, etc.
• Proven experience leading large-scale data migrations (ETL, workloads, cloud platforms), including migration of legacy data platforms or ETL workloads to cloud-native environments.
• Experience applying CI/CD practices to data engineering workflows, including version control, automated deployment, and pipeline orchestration.
• Independent ability to review the data quality and data definitions and perform data cleansing and data management tasks.
• Experience collaborating within cross-functional and multi-disciplinary teams to solve complex data challenges, including processing semi-structured and unstructured data
• Experience in at least one major cloud service: AWS, Azure and GCP with understanding of cloud-native services, identity management, and scalable architecture principles.

• Certifications: Databricks Certified Data Engineer (Associate or Professional) and/or relevant cloud certifications (e.g., Azure, AWS, or GCP architecture or data engineering credentials) are preferred.

KPMG Ontario Region Pay Range Information

The expected base salary range for this position is $77,000 to $102,000 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.

KPMG BC Region Pay Range Information   

The expected base salary range for this position is $73,000 to $100,000 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. 

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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

Weembrace 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.

• University degree in computer engineering, mathematics, data science or related disciplines
• 4+ years of professional experience in a related field like Data Engineering, Business Intelligence, or related field with a track record of manipulating, processing, and extracting value from large datasets.
• 2+ years of hands-on experience with Databricks, including advanced features (Delta Lake, Unity Catalog) with Databricks or cloud certifications with 1-2 years of experience leading workstreams / client-facing delivery.
• Strong proficiency in SQL and solid understanding of modern data modeling principles, dimensional modeling, and data warehousing concepts.
• Proficiency in Python (or similar scripting languages) for data processing, automation, and analytical workflows
• Strong experience working in teams to perform ETL (extract, transform and load) of data from a variety of databases from SQL, NoSQL, etc.
• Proven experience leading large-scale data migrations (ETL, workloads, cloud platforms), including migration of legacy data platforms or ETL workloads to cloud-native environments.
• Experience applying CI/CD practices to data engineering workflows, including version control, automated deployment, and pipeline orchestration.
• Independent ability to review the data quality and data definitions and perform data cleansing and data management tasks.
• Experience collaborating within cross-functional and multi-disciplinary teams to solve complex data challenges, including processing semi-structured and unstructured data
• Experience in at least one major cloud service: AWS, Azure and GCP with understanding of cloud-native services, identity management, and scalable architecture principles.

• Certifications: Databricks Certified Data Engineer (Associate or Professional) and/or relevant cloud certifications (e.g., Azure, AWS, or GCP architecture or data engineering credentials) are preferred.

KPMG Ontario Region Pay Range Information

The expected base salary range for this position is $77,000 to $102,000 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.

KPMG BC Region Pay Range Information   

The expected base salary range for this position is $73,000 to $100,000 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