Quality Engineer

Requisition ID: 275896

At Tangerine, we’re redefining banking. As Canada’s leading digital bank, we thrive on innovation, agility, and bold thinking, tackling every challenge head-on with leading technology and the unstoppable power of collaboration. 

Our client-obsessed teams deliver flexible, accessible banking solutions, breakthrough products, and award-winning service. Beyond banking, we’re committed to making an impact in the communities we serve and across our organization. We foster a culture built on integrity, inclusion, and fearless ambition – where diverse perspectives are valued, and people are empowered to do their best work. 

Are you ready to disrupt the status quo? Do you crave challenges that push boundaries? If you’re a high performer looking to accelerate your career and reimagine the banking landscape, this is your moment. 

Let’s shape the future of banking together! 

Do you like new challenges? Are you ready to reach new heights in your career and become part of an established disruptor? If so, come join us and help redefine the Canadian banking landscape! 

We are looking for a Senior Quality Engineer to join our Quality Engineering team. This person will be responsible for ETL testing, data validation, source-to-target reconciliation, data transformation testing, and end-to-end validation of data pipelines in Data Warehouse environments.

Is this role right for you? In this role, you will:

• Collaborate with developers, business analysts, data engineers, and other stakeholders to identify, troubleshoot, and resolve data quality issues.
• Participate in requirements reviews, source-to-target mapping sessions, and design discussions to ensure testability, completeness, and data quality.
• Analyze source-to-target mappings, define test strategies, create comprehensive test cases, and perform rigorous data validation.
• Validate data accuracy, completeness, and integrity through source-to-target reconciliation and transformation testing.
• Execute complex SQL queries, perform backend testing, and validate ETL transformations across Oracle, SQL Server, and BigQuery platforms.
• Validate end-to-end ETL workflows, data pipelines, and data movement across source, staging, and target environments.
• Work with multiple source systems containing structured, semi-structured, and JSON data.
• Develop and maintain automated data validation, reconciliation, and regression tests using Python, SQL, and other automation utilities.
• Support continuous improvement of ETL testing processes through automation and reusable testing frameworks.
• Own test planning, test execution, defect management, regression validation, test reporting, and testing sign-off for assigned EDW initiatives.