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.
Data Engineer • Toronto, CA
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