Data Engineer to design, develop, and optimize scalable data pipelines

Data Engineer 3 days a week in office Downtown Toronto Collaborate with business teams and Data Analysts to gather and understand requirements, ensuring alignment with business objectives and data needs. Translate business needs into detailed technical requirements in collaboration with subject matter experts (SMEs) to ensure accuracy and feasibility. Recommend and design scalable, efficient, and effective data architectures and workflows to support current and future business requirements. Design, develop, and maintain data assets to enable seamless extraction, transformation, and loading (ETL/ELT) processes from diverse data sources, making data accessible to client-facing applications, data warehouses, and internal tools. Implement and enforce best practices for observability, data lineage, and governance, ensuring transparency, reliability, and compliance across all data systems. Experience Professional experience in data engineering, with a strong focus on designing, developing, and optimizing scalable data pipelines, ETL/ELT workflows, and data integration solutions using modern tools and technologies. Must haves: Understanding of data pipeline architecture, modern data stack architecture, and cloud-based platforms, including AWS, Snowflake, and other cloud-native solutions. In-depth knowledge and experience with the following tools and concept: o Data extraction - SQL, Python, API invocation o Database systems - PostgreSQL, MySQL o Data storage repositories - SFTP, AWS S3 o ETL/ ELT tools and workflow - Snowflake, PySpark, AWS Glue, AWS Lambda o CI/CD pipelines - Bitbucket, Git, Jenkins, CloudFormation Experience in the Financial Services Industry is an asset. Apply

Location: Toronto, Ontario, CA

Posted Date: 7/6/2025