BMO is currently sourcing for a Data Quality Engineer, to support the Financial Crimes Unit.This is a hybrid contract role in Toronto (2 to 3 days in office per week). Role Overview This role supports the modernization of the data quality framework for fraud and financial crimes data. As the fraud data warehouse moves from an on-prem environment to AWS, the team is shifting from after-the-fact data quality checks toward automated, embedded monitoring. The Data Quality Engineer builds the rules, alerts and workflows that identify data issues earlier and reduce manual resolution. The role focuses on data management and governance rather than QA or testing, and works with business stakeholders at senior levels.
Key Responsibilities
Design and build data quality rules and automated alerts across customer, account and transaction data Query, profile and prepare large datasets using SQL and Python Modernize the existing data quality framework as data moves from on-prem to AWS Develop automated and AI-enabled workflows to replace manual data issue resolution Document and catalog data as part of data governance practices Gather requirements and partner with senior business stakeholders on data issues Lead the data quality domain end to end as the primary point of contact
Must-Have Skills
7+ years of experience in data quality, data management or data governance at a senior level Hands-on SQL and Python (or R) for working with large datasets Hands-on experience building data quality rules and automated data quality alerts Hands-on experience with data quality and BI tools, with the ability to work across multiple tools Data governance and data management fundamentals, including data cataloging Working knowledge of cloud data environments, AWS preferred
Nice to Have Skills
Prior BMO experience Experience at a financial institution, ideally a Canadian big five bank Fraud or financial crimes domain experience Exposure to Sybase IQ or on-prem to cloud data migrations Exposure to AI or automation workflows for data issue resolution Exposure to Splunk or cyber data
Ideal Candidate
Has worked with enterprise-scale banking data volumes Has designed data quality solutions across several tools rather than specializing in one product Has a data governance background that gives context on how data is sourced, used and impacted Has led data quality or data management work with director-level stakeholders
