Sr Data Engineer

Iris's direct client, one of the Top 5 Bank in Canada, is looking to hire a Sr Data Engineer a long-term opportunityat Toronto, ON (Hybrid).

Our client is a Canadian multinational financial services company and the largest bank in Canada by market capitalization. The bank serves over 17 million clients and has more than 89,000 employees worldwide. Bank is serving individual consumers, small and middle market businesses and large corporations with a full range of banking, investing, asset management and other financial and risk-management products and services.

Location: Toronto, ON (Hybrid)

Duration: Long Term (12+ Months)

Required Skill

• Design and validate migration patterns from legacy Netezza/SSIS ETL to AWS-native pipelines (Glue, PySpark, S3, Redshift, Lambda etc.)
• Provide hands-on architecture and coding guidance — this is a working architect role, not purely advisory
• Own data migration reconciliation strategy (source-to-target validation, PII/sensitive data handling, encryption)
• Design for regulatory reporting requirements (auditability, lineage, data quality controls) typical of retail/wholesale enterprise risk platforms
• Optimize Redshift schema/performance and Glue/PySpark job design for regulatory batch and reporting workloads
• Support integration with downstream risk model consumption patterns (e.g., model inference pipelines, scoring APIs)

Required Technical Skills

• 8+ years hands-on data engineering experience, including production ownership
• Proven experience designing and executing large-scale data migrations (legacy MPP ? cloud lakehouse / warehouse)
• Strong SQL and data modeling skills (dimensional and normalized models)
• Experience with data quality, reconciliation, and validation frameworks for regulated data
• Familiarity with encryption/PII handling and data governance controls

Understanding of CI/CD and orchestration tooling (Airflow, Glue workflows, or equivalent