We are seeking a Data Analyst IV to join our Data Engineering team within the GWAM Data Office. This role is ideal for a motivated and technically skilled individual with strong analytical and leadership capabilities who is passionate about data, technology, and customer-centric innovation. You will lead requirements gathering, conduct complex data analysis, and ensure the successful delivery of enterprise-level data projects aligned with business needs and strategic goals. Key Responsibilities Lead business requirements sessions, collaborate with stakeholders, and secure sign-offs. Develop and maintain key documentation including Business Requirements Documents (BRDs), Source-to-Target Mappings (STMs), and other data analysis deliverables. Act as the liaison between business stakeholders, project teams, and technical teams to ensure alignment and delivery of valuable data assets. Conduct data profiling, metadata collection, and comprehensive data analysis to support project initiatives. Lead User Acceptance Testing (UAT) activities and obtain final approval from business users. Ensure all data solutions are aligned with organizational strategy and provide real business value. Required Qualifications 7–10 years of experience as a Data Analyst, preferably in Wealth Management (e.g., Retail, Retirement, Institutional, or General Accounts). 2–3 years of hands-on experience with GenAI and Azure Cloud platforms. Experience with data-centric projects in capital markets or investment banking, including: Master Data Management Data Integration Data Warehousing Reporting platforms Proficiency in writing and optimizing complex SQL queries for data analysis and validation. Demonstrated experience delivering complete data documentation artifacts within tight project timelines. Strong verbal and written communication skills; able to clearly articulate data requirements and insights across all organizational levels. Familiarity with major financial and trading platforms, including: SimCorp Dimension Findur Apex Sylvan Calypso Experience developing data infrastructure within data lakes or data warehouse environments. Strong knowledge of data modeling, data profiling, validation, and ETL using SQL scripts. Expertise in integrating new data sources into enterprise data ecosystems. Preferred Qualifications Background in large-scale financial services or investment firms. Certifications in data analytics, cloud platforms (Azure), or business analysis. Certifications None required, but relevant data or cloud certifications (e.g., Azure Data Engineer, CBIP, CBDA) are a plus. Email ID * This field is required Please enter valid emailId.Cell phone * This field is required Please enter valid cell phone. First Name * This field is required Please enter valid first name. Last Name * This field is required Please enter valid last name. #J-18808-Ljbffr