AVP, Data Product Owner – Wealth Management (Data Products)

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AVP, Data Product Owner – Wealth Management (Data Products)

Location

Hybrid / Onsite as required

Reports To

VP / Strategic Data Lead

Role Summary

LPL Financial is seeking an Assistant Vice President, Data Product Owner (DPO) to own and manage individual Wealth Management (WM) data products. This role is responsible for day-to-day ownership, execution, and governance of assigned datasets, ensuring they are accurate, usable, and aligned with business needs.

The AVP DPO operates as the hands-on product owner, working closely with engineering, data stewards, and business stakeholders to define requirements, manage data quality, and drive adoption.

This is not a reporting or analytics role — it is an execution-focused data product ownership role with clear accountability for data quality, usability, and governance.

Key Objectives

• Establish clear ownership for assigned WM data products
• Deliver well-defined, governed, and consumable datasets
• Improve data quality and trust at the product level
• Embed governance into delivery workflows and backlog execution
• Support enterprise initiatives with high-quality data products

Core Responsibilities

1. Data Product Ownership & Execution

• Act as the named Data Owner for specific WM data products
• Define and maintain:
  • Business definitions and metadata
  • Use cases and data consumers
  • Data quality rules and thresholds
• Make decisions on:
  • Fitness-for-purpose for assigned datasets
  • Data access approvals (within defined guardrails)
  • Prioritization of enhancements within backlog

2. Wealth Management Domain Support

• Own data products within WM domains such as:
  • Clients / Participants
  • Accounts and transactions
  • Securities and pricing
• Serve as primary point of contact for consumers
• Ensure data supports operational and regulatory use cases

3. Data Product Lifecycle Management

• Execute lifecycle activities:
  • Define → Build → Publish → Operate → Enhance
• Maintain artifacts:
  • Data Product Charter and Canvas
  • Product backlog and roadmap
• Partner with delivery teams to ensure:
  • Requirements are clear and actionable
  • Data considerations are embedded in delivery

4. Data Quality & Issue Management

• Identify and track Critical Data Elements (CDEs)
• Define data quality rules with Data Stewards
• Monitor data quality metrics and trends
• Drive remediation of data issues and defects
• Escalate material risks to VP-level leadership

5. Technical Partnership

• Work closely with Data Custodians and Engineering to:
  • Review data structures, transformations, and lineage
  • Support schema and contract changes
  • Translate business requirements into specifications
• Utilize data governance and catalog tools

6. Cross-Functional Collaboration

• Collaborate with:
  • Data Stewards
  • Engineering and platform teams
  • Risk, Compliance, and Legal
• Support enterprise initiatives by ensuring data readiness and clarity

Required Qualifications

Experience

• 6–10+ years in Wealth Management or Financial Services
• Experience in:
  • Data product ownership, product management, or data governance
  • Working within large, complex enterprise environments

Wealth Management Expertise

• Strong understanding of WM data domains and use cases
• Familiarity with WM business processes and regulatory considerations

Technical Knowledge

• Working knowledge of:
  • Data modeling, pipelines, and transformations
  • Data quality and reconciliation concepts
  • Metadata, lineage, and catalog tools
• Ability to effectively partner with technical teams

Key Attributes

• Strong ownership mindset and attention to detail
• Execution-focused and solution-oriented
• Clear communicator across business and technical teams
• Comfortable working in structured governance environments

What Success Looks Like (12–18 Months)

• Clear ownership and documentation for assigned data products
• Improved data quality metrics and reduced data defects
• Increased adoption and reuse of governed datasets
• Strong partnership with engineering and data stewards
• Effective contribution to enterprise data initiatives

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