Business Analysis Manager - Data Quality and Remediation

Define, document, and drive changes required to the data model in support of the firm's strategic agenda, ensuring clear communication and timely delivery.

Lead collaboration with Technology and Remediation teams to prioritize data remediation programs and ensure data is in good order to support strategic business initiatives.

Facilitate alignment between business users and data owners to ensure comprehensive understanding of data structures, definitions, and usage.

Develop and deliver executive-level presentations and materials for stakeholder reviews, project team meetings, and leadership forums.

Build and manage strategic partnerships across Operations, Technology, Business Management, and Advisory functions.

Drive cross-functional collaboration across Lines of Business, Compliance, and Technology to conduct root-cause analysis and define strategic remediation paths for data quality issues across critical WM applications.

Serve as the primary subject matter expert for WM Data Quality, providing guidance and support across teams on ad hoc and strategic data issues.

Own documentation of resolution processes and procedures, ensuring effective handover to Operations upon completion.

Establish and govern data quality metrics and KPIs across Lines of Business and relevant data sources.

Lead, mentor, and develop a high-performing team, fostering a culture of accountability, continuous improvement, and data excellence.

Domain Expertise: Strong understanding of Wealth Management and financial services data domains, with experience across areas such as client onboarding, KYC, relationship maintenance, authorities and limits, sales management, and regulatory data requirements.

Technical Expertise: In-depth knowledge of data models, principally party and account data stores and associated system feeds, with familiarity in extracting, visualizing and analyzing complex data sets using tools such as Alteryx, Tableau, Qlik, or SQL Server.

AI & Emerging Technology Proficiency: Demonstrated ability to leverage AI and machine learning tools for data quality analysis, pattern recognition, and remediation automation; experience with AI-powered analytics platforms and prompt-based tools to accelerate data diagnostics and executive reporting.

Communication & Stakeholder Management: Exceptional verbal and written communication skills with experience engaging senior stakeholders and translating complex data issues into actionable business outcomes. Based on existing communication requirements in the role description.

Analytical & Problem-Solving Skills: Strong analytical and critical-thinking skills with the ability to develop and clearly present conclusions and solutions with consideration to inherent risks.

Leadership: Proven ability to lead teams, manage multiple priorities, and deliver results in a complex and highly collaborative environment.