University degree in computer engineering, mathematics, data science or a related field
4+ years in Data Engineering or Business Intelligence with large datasets
2+ years of hands-on experience with Databricks and client-facing delivery
Strong SQL proficiency and understanding of data modeling principles
Proficiency in Python for data processing and automation
Experience leading large-scale data migrations to cloud environments
Familiarity with CI/CD practices applied to data engineering workflows
Responsibilities
Partner with clients to define business goals and develop technical designs
Translate analytics requirements into a data strategy, including ETL/ELT processes
Contribute to solution architecture for cost-optimized implementation
Lead delivery of data platforms on Databricks, focusing on ETL pipelines and workload migrations
Implement Delta Lake patterns and maintain data quality controls
Design scalable batch and streaming data pipelines using Spark
Support testing and production releases with troubleshooting and performance tuning
Benefits
Opportunities for professional growth and development
Access to comprehensive Total Rewards program
Potential for bonus awards
Work collaboratively in cross-functional teams
Engage in challenging projects that solve complex data challenges
Full Job Description
What you will do
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.
What you bring to the role
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.
