About this role
Data Quality Engineer-Cards Engineering, Transactional Services and Data Services Engineering
Requisition ID: 255249
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture. Scotiabank continues to be an industry leader for Payment’s technology and innovation. We have a history of safely leveraging new tools to enable new experiences for our customers, focusing on ensuring we protect their interests and goals. The result of this leads to modernization programs which aim to offer enriched information and transparencies to support the rapidly evolving payments community.
Purpose
As a Data Quality Engineer within the Cards Engineering team, you will lead and coordinate quality assurance efforts for small to large-scale initiatives across multiple delivery channels and platforms. Operating within an Agile delivery model, you will champion system reliability, drive automation-first testing strategies, and ensure that quality is embedded throughout the software development lifecycle. You will assess the risk and impact of changes across a portfolio of over 190 banking applications and processes supporting the domestic bank network. Reporting to the Senior Manager QA, you will collaborate with cross-functional squads(teams), including developers, product owners, and analysts, to deliver secure, scalable, and high-performing solutions
What You’ll Do
- Leads and drives a customer focused culture throughout their team to deepen client relationships and leverage broader Bank relationships, systems and knowledge.
- Understand how the Bank risk appetite and risk culture should be considered in day-to-day activities and decisions.
- Lead QA planning and execution across Agile squads, ensuring alignment with sprint goals and release timelines.
- Design, develop, and execute data quality validation for ETL pipelines across relational and big data platforms.
- Validate source-to-target mappings, transformation logic, and business rules.
- Perform SQL-based data analysis and reconciliation using DB2, Hive, and related data stores.
- Develop and maintain Python-based data quality frameworks, validation scripts, and automation.
- Identify, analyze, and report data quality iss