Data Analyst IV Job Toronto area,Ontario Canada,IT/Tech

We are on a journey to become a customer-centered digital leader and are seeking a motivated Senior Data Analyst to help drive strategic initiatives. Reporting to the Lead Data Analyst in the GWAM Data Office/Engineering team, you will work cross-functionally to ensure delivery of high-impact, data-driven projects in Wealth Management. Your work will align with our broader data strategy, leveraging modern technologies and best practices.

Job Responsibilities:

Lead business sessions to gather, clarify, and validate data requirements

Create and maintain Business Requirement Documents (BRDs), Source-to-Target Mappings (STM), and metadata documentation

Ensure data solutions meet business expectations and align with strategic goals

Liaise across stakeholders to gain consensus and support data-related initiatives

Conduct in-depth data analysis, profiling, and validation activities

Manage UAT activities, including test planning, execution, and user sign-off

Provide support and guidance on data modeling, integration, and transformation

Contribute to building scalable, flexible data infrastructure and pipelines

Required Skills:

5–10 years of experience as a Data Analyst in Wealth Management (Retail, Retirement, Institutional, or General Accounts)
2–3 years of hands-on experience with GenAI
Working knowledge of Adobe Journey Optimizer
Proven experience in master data management, data integration, data warehousing, and analytics in capital markets or investment banking environments
Strong SQL skills for data querying, profiling, validation, and transformation
Proven experience delivering documentation artifacts in large, complex environments
Strong communication skills, both written and verbal, with stakeholders at all levels
Experience with trading platforms and book of record systems such as Bloomberg Polar Lake, Sim Corp Dimension, Findur, Apex, Eagle, Charles River, Sylvan, Calypso
Business analysis experience in building or managing data lakes or data warehouses
Expertise in data modeling, ETL processes, and loading/validating datasets using SQL
Ability to integrate new data sources into existing platforms (lake/warehouse)

Preferred

Skills:

Exposure to Azure cloud technologies
Experience with AWS Connect
Background in Agile teams and methodologies
Experience using big data technologies and analytics frameworks

Certifications:

[Specify if required or preferred – e.g., Certified Data Analyst, Azure Data Engineer Associate]

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