VP, Data Product Owner – Advisor System of Record

Role Overview

• Define and execute the Advisor SOR product vision, roadmap, and backlog
• Establish canonical advisor data models, hierarchies, and relationships
• Define and manage: Data contracts (schema, SLAs, versioning)
• Critical data elements (CDEs)
• Data quality SLOs
• Serve as the authoritative decision-maker for advisor data definitions and product scope
• Implement scalable frameworks for: Data quality monitoring and remediation
• Reconciliation and defect management
• Lineage and impact analysis
• Partner with Data Governance to ensure: 100% catalog coverage of critical advisor attributes
• Policy-to-control alignment
• Audit and regulatory readiness
• Ensure Advisor SOR is optimized for AI and advanced analytics use cases
• Partner with AI Business Solutions and Data Science teams to: Define feature-ready datasets and semantic layers
• Support AI agents and copilots with high-quality advisor data
• Leverage modern AI-enabled development tools, including: Cursor (AI-assisted coding and development workflows)
• GitHub (code management, CI/CD, and collaboration)
• Anthropic tools (Claude-based workflows, prompt engineering, agent design)
• Contribute to development of agentic workflows and AI-driven automation across advisor lifecycle processes
• Lead hydration of advisor data into Strategic SOR platforms
• Partner with Technology to: Build scalable data pipelines, APIs, and distribution layers
• Ensure platform performance, reliability, and scalability
• Support M&A and migration initiatives, including: Source-to-target mapping
• Mock conversions and validation
• Cutover readiness and reconciliation
• Identify and onboard priority consumers: Advisor platforms
• Operations workflows
• AI/analytics use cases
• Develop: Migration and onboarding playbooks
• Legacy decommission strategies
• Partner with Data Distribution and consumer teams to ensure seamless adoption
• Design and implement scalable patterns: Data contracts
• Automated quality frameworks
• Reusable lineage and reconciliation models
• Contribute to AI-enabled product innovation and workflow automation
• Familiarity with FINRA, SEC, and privacy requirements impacting advisor data

Requirements

• 10–15+ years in data, product, or domain roles within Wealth Management or Financial Services
• 7 plus years experience owning or delivering enterprise data products or systems of record
• Experience with Domain-driven design
• Data product operating models (DPO frameworks)
• Metadata/catalog and observability tools
• Exposure to M&A integrations or platform consolidations
• AI/ML-enabled products or automation initiatives
• Deep understanding of Wealth Management advisor data, including: Advisor identity, hierarchy, and book of business Relationships to clients, accounts, positions, and transactions
• Strong knowledge of Data modeling (conceptual, logical, canonical)
• Data contracts and APIs
• Data quality, lineage, and reconciliation
• Hands-on or strong working knowledge of Cursor (AI-assisted development workflows)
• GitHub (version control, CI/CD, collaboration)
• Anthropic tools (e.g., Claude) for prompt engineering, agent workflows, and productivity
• Familiarity with AI/ML data requirements
• Feature engineering and semantic layers
• Agentic workflow design and automation patterns

Benefits

• 401K matching
• health benefits
• employee stock options
• paid time off
• volunteer time off