Senior BSA & Solutions Lead for Bank Risk Data

RBC; Toronto; On-site; CAD 100,000 - 140,000; Full time

Job summary

RBC in Toronto is seeking a Senior Business Systems Analyst to lead requirements gathering for large-scale Credit Risk Reporting initiatives within Global Functions Technology. You will coordinate with business stakeholders, development and QA teams to ensure timely delivery of data-intensive solutions.

The role emphasizes collaboration, data modeling, and leveraging AI tools to streamline the SDLC while delivering compliant, scalable risk reporting platforms.

Qualifications

• Undergraduate degree or higher in Mathematics, Computer Science, Engineering or Finance.
• 5+ years as a Senior BSA in banking delivering system implementations or integrations.
• Deep understanding of banking book and trading book products.
• Advanced SQL with strong data analysis and root-cause problem solving.
• Proficiency with JIRA, Confluence, SQL; ability to leverage AI tools (GitHub Copilot, RBC Assist).

Responsibilities

• Lead BSA activities across analysis and design; govern adherence to enterprise requirements methodology.
• Elicit, document, and manage requirements (system specs, data catalogs, use cases) for medium–large initiatives.
• Analyze data integration options; assess materiality and impact of data quality issues; recommend solutions.
• Contribute to data model and solution architecture decisions for high-volume risk data.
• Support development and QA through the SDLC; identify risks and drive mitigation to deliver on time and on budget.

Skills

Advanced SQL

Data analysis

Stakeholder collaboration

Leadership

JIRA

Confluence

GitHub Copilot

RBC Assist

Python

Education

Undergraduate degree or higher

Tools

JIRA

Confluence

SQL

GitHub Copilot

RBC Assist

Job description

RBC in Toronto is seeking a Senior Business Systems Analyst to lead requirements gathering for large-scale Credit Risk Reporting initiatives within Global Functions Technology. You will coordinate with business stakeholders, development and QA teams to ensure timely delivery of data-intensive solutions.

The role emphasizes collaboration, data modeling, and leveraging AI tools to streamline the SDLC while delivering compliant, scalable risk reporting platforms.