We are looking for an experienced Data Engineer to build and enhance modern data solutions that support finance-focused business priorities in Toronto, Ontario. This position combines hands-on engineering with technical leadership to strengthen data pipelines, improve model consistency, and enable trusted reporting and advanced analytics. The successful candidate will help modernize legacy data environments within a cloud-based Lakehouse architecture while promoting strong governance, security, and scalability across enterprise data platforms.
What you'll be working on:
• Design, build, and maintain scalable data pipelines and integrations that support finance data products and downstream reporting needs.
• Lead the modernization of legacy finance data environments by moving critical datasets and workflows into Azure-based Lakehouse platforms.
• Develop reusable engineering frameworks and standardized data models to improve consistency, efficiency, and long-term maintainability.
• Collaborate with cross-functional stakeholders to connect finance data assets with broader enterprise platforms for analytics, planning, and AI-driven use cases.
• Apply data governance, security, and quality standards throughout the data lifecycle to ensure reliable and compliant solutions.
• Optimize data processing performance for large and complex datasets using tools such as Databricks, PySpark, and Azure-native services.
• Support the delivery and ongoing enhancement of business intelligence solutions, including data structures used for Power BI reporting.
• Contribute to platform administration and technical best practices across Azure data services, while documenting work and tracking delivery through project tools.
• Identify opportunities to streamline data processes and implement improvements that increase operational efficiency and solution reliability.
Key Requirements:
• Bachelor’s degree required; a graduate degree in engineering or a related discipline is considered an asset.
• Minimum of 7 years of experience in data engineering, including significant work within Microsoft Azure environments.
• Strong hands-on expertise with Azure services such as Databricks, Synapse, Cosmos DB, Function Apps, Logic Apps, Azure Data Factory, and Azure Data Lake.
• Proven experience designing and supporting Lakehouse solutions using Databricks.
• Advanced programming and data processing skills in Python, PySpark, or Scala.
• Solid SQL skills with a demonstrated ability to work effectively with large and complex datasets.
• Experience with data governance platforms and practices, along with an understanding of security and compliance requirements.
• Familiarity with Power BI delivery and support, as well as working knowledge of collaboration and tracking tools such as Confluence, Jira, and TestRail.
This is a hybrid role that will require you to be in-office 3 to 4 days a week.
Robert Half is the world’s first and largest specialized talent solutions firm that connects highly qualified job seekers to opportunities at great companies. We offer contract, temporary and permanent placement solutions for finance and accounting, technology, marketing and creative, legal, and administrative and customer support roles.
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Data Engineer • Toronto, ON, CA
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