LPL Financial

VP, Data Product Owner – Advisor System of Record

LPL Financial

full-time

Posted on:

Location Type: Office

Location: New York City • New York • Texas • United States

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Salary

💰 $145,925 - $243,209 per year

Job Level

Lead

About the role

  • 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
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
data modelingdata contractsdata qualitylineagereconciliationfeature engineeringsemantic layersAI/ML-enabled productsautomationdomain-driven design
Soft Skills
leadershipdecision-makingcollaborationcommunicationorganizational skillsproblem-solvingstrategic thinkingadaptabilityanalytical skillsproject management