Job Overview:

LPL Financial is seeking an Assistant Vice President, Data Product Owner (DPO) to own and manage Wealth Management data products. This individual contributor role is responsible for the day-to-day ownership, execution, and governance of assigned datasets, ensuring they are accurate, usable, and aligned with business needs. The role partners closely with engineering, data stewards, and business stakeholders to define requirements, manage data quality, support governance activities, and drive adoption of high-quality data products across the organization.

Responsibilities:

• Serve as the named Data Owner for assigned Wealth Management data products.

• Define and maintain business definitions, metadata, data product documentation, use cases, and consumer information.

• Establish and maintain data quality rules, thresholds, and monitoring practices in partnership with Data Stewards.

• Evaluate datasets for fitness-for-purpose and support data access decisions within established governance guardrails.

• Prioritize and manage enhancements through the data product backlog and roadmap.

• Act as the primary point of contact for consumers of assigned data products.

• Support Wealth Management domains including clients/participants, accounts and transactions, and securities and pricing.

• Ensure data products support operational, business, and regulatory use cases.

• Execute data product lifecycle activities including defining, building, publishing, operating, and enhancing data products.

• Maintain data product artifacts such as product charters, product canvases, backlogs, and roadmaps.

• Partner with delivery teams to ensure requirements are documented and actionable.

• Identify and manage Critical Data Elements (CDEs).

• Monitor data quality metrics and trends and drive remediation of data defects and issues.

• Escalate material data risks to appropriate leadership when necessary.

• Collaborate with engineering and data custodians to review data structures, transformations, lineage, and schema changes.

• Translate business requirements into technical specifications.

• Utilize enterprise data governance and data catalog tools.

• Partner with Risk, Compliance, Legal, and other stakeholders to support enterprise initiatives requiring trusted data products.

What are we looking for?

We’re looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidatespursue greatness,act with integrity, and aredriven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where wewin togetherandcreate and share joyin our work.

Requirements:

• 6 610+ years of experience in Wealth Management or Financial Services.

• Demonstrated proficiency using AI tools and platforms to identify and drive automation opportunities across data products.

• Experience designing, creating, updating, and onboarding AI-driven agents to streamline workflows and improve operational efficiency.

• Experience integrating AI capabilities into existing data product frameworks, including optimization and governance activities.

• Understanding of emerging AI use cases and the ability to translate them into scalable, business-aligned solutions.

Core Competencies:

• 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.

• Establish clear ownership for assigned WM data products.

Preferences:

• Strong understanding of Wealth Management data domains and use cases.

• Experience with data product ownership, product management, or data governance.

• Experience working with data quality management, metadata management, and data governance practices.

• Experience collaborating with engineering, platform, risk, compliance, and legal stakeholders.

• Experience supporting wealth management data domains such as clients, participants, accounts, transactions, securities, and pricing.

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