Databricks Data Engineer
Summary
Senior data engineer who designs, builds, and optimizes scalable enterprise data pipelines and data models using Databricks (PySpark, Delta Lake, Unity Catalog, Lakeflow) and AWS (S3, Glue, Lambda, Step Functions, Redshift), supporting financial data platforms like Advisor360, ETF, and mutual fund solutions. Hybrid role based in Toronto (3 days in office).
Hi,
Job role— Databricks Data Engineer
Location: Toronto, Canada -Hybrid — 3 days Tuesday to Thursday work from office, 2 days Monday and Friday remote
Senior Data Engineer
Role Overview
We are seeking a highly experienced Senior Data Engineer with strong expertise in Databricks, AWS, modern data architecture, and data modeling to design and build scalable enterprise data platforms. The role will lead the development of data pipelines, analytical assets, and data foundations supporting platforms such as Advisor360, CRM, ETF, and Mutual Fund data solutions. This is a senior-level, autonomous role requiring strong technical leadership, consultative problem-solving, and architecture expertise.
Key Responsibilities
Design, develop, and optimize scalable data pipelines using Databricks (PySpark, Delta Lake, Unity Catalog, Lakeflow) and AWS (S3, Glue, Lambda, Step Functions, Redshift).
Lead data ingestion, transformation, and modeling initiatives for enterprise data platforms.
Define and implement robust data models supporting analytics, reporting, and AI/ML use cases.
Gather and translate complex business requirements into scalable technical solutions.
Establish data quality, monitoring, testing, and operational best practices across data platforms.