Payments Data Analyst (3–7 years)

Our financial services client is seeking a Payments Data Analyst (3–7 years) to modernize payment operations using automation and AI-enabled solutions

Join a payments-focused portfolio within a broader infrastructure, architecture, and modernization line of business driving payment transformation and delivery. This role supports the Alternative Solutions Group by advancing automation, intelligent reconciliation, test automation, and AI-driven initiatives across payment platforms. The engagement is a 12-month contract starting in early December with hybrid onsite work on Mondays and Tuesdays and potential for extension.

Contract, Toronto, Hybrid,  2 days, Mondays and Tuesdays

81 Bay Street

12 months

Must Have Requirement:

• Experience in payments operations, reconciliation, exception management, and settlement processes.

• Strong background in process automation using Python, SQL, Power Automate, Alteryx, UiPath, or similar tools.

• Experience with test automation, including SIT, UAT, and regression testing.

• Strong data analytics, reporting, and dashboard development skills.

• Experience with AI-enabled solutions and intelligent automation initiatives.

• Proven ability to partner with cross-functional stakeholders and deliver scalable solutions.

• Strong analytical, problem-solving, and communication skills.

Nice to Have:

• Worked on large transformation programs

• • Top 5 banking experience.

Responsibilities

• Design automated workflows for payment operations, reconciliation, exception management, and operational controls.
• Implement automation initiatives using Python, SQL, Power Automate, Alteryx, UiPath, or similar platforms.
• Develop and maintain automated test cases and regression testing frameworks for payment systems and operational platforms.
• Support SIT, UAT, regression testing, and reconciliation validation.
• Support reconciliation and balancing activities across real-time payments, wires, ACH/EFT, card payments, ISO messaging, and settlement processes.
• Analyze operational and payment data to identify trends, inefficiencies, control gaps, and automation opportunities.
• Build dashboards, reporting solutions, and operational metrics to monitor performance and inform decision-making.