Data Analyst IV

Job Summary:

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, SimCorp 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]

Education: Bachelors Degree

Certification: Certified Data Analyst