AVP, Data Product Owner

LPL Financial•Charlotte, NC

About The Position

LPL Financial is seeking a Data Product Owner to lead product ownership for consumption-facing data capabilities. The role focuses on how enterprise data is discovered, understood, accessed, and used by downstream consumers across applications, analytics platforms, advisor experiences, operations, partners, and enterprise reporting. Operating at the intersection of Product Management, Data Product Ownership, Consumer Enablement, and Data Analysis, this position defines product strategy, maintains roadmaps, aligns stakeholders, and ensures enterprise data capabilities deliver measurable business outcomes. The role partners across business, data, engineering, architecture, governance, and platform teams to create scalable, trusted, and reusable data products that improve data consumption across the enterprise. The ideal candidate combines product management discipline, analytical problem-solving, data fluency, and stakeholder engagement to advance enterprise data consumption capabilities. The role is suited to a professional motivated to pursue greatness, act with integrity, help clients succeed, collaborate effectively, and deliver meaningful business outcomes.

Requirements

5+ years of experience in Product Management, Product Ownership, Data Product Ownership, Product Analytics, Data Analysis, or platform-oriented product roles.
Demonstrated experience defining product strategy, product vision, roadmaps, priorities, and success measures.
Strong hands-on experience with SQL, data analysis, source-to-target analysis, or analytical problem-solving across distributed data environments.
Experience working with data platforms, data distribution capabilities, APIs, feeds, integration layers, reporting platforms, or shared enterprise data services.
Experience operating in Agile/Scrum environments with cross-functional product, engineering, QA, architecture, and stakeholder teams.

Nice To Haves

Ability to translate complex data ecosystems and consumer needs into clear product requirements.
Understanding of data quality, data lineage, metadata, semantic consistency, data contracts, data governance, and downstream impact analysis.
Strong communication skills and ability to influence stakeholders and explain technical concepts in business-friendly language.
Experience using AI-enabled capabilities to improve the speed, depth, and effectiveness of data analysis, requirements development, or product discovery.
Experience creating product narratives, roadmap readouts, value statements, adoption metrics, and executive-level decision support materials.

Responsibilities

Define and maintain product vision, strategy, and multi-quarter roadmaps for consumption-facing data capabilities.
Translate business outcomes, consumer needs, and enterprise data strategy into prioritized product initiatives.
Establish product success measures, KPIs, and OKRs to evaluate adoption, reliability, usability, and business impact.
Engage downstream consumers to gather requirements, identify pain points, and define data product use cases.
Develop user stories, acceptance criteria, release objectives, and consumption requirements that are clear and testable.
Define and support data access patterns through APIs, feeds, reporting platforms, extracts, and shared services.
Prioritize and manage product backlogs, balancing strategic initiatives, consumer demand, operational needs, and delivery capacity.
Partner with engineering, architecture, governance, and domain teams to deliver scalable and reusable data capabilities.
Perform data analysis to understand usage patterns, source-to-target relationships, lineage, dependencies, and impacts.
Conduct impact assessments for schema changes, new integrations, platform migrations, and upstream system modifications.
Use SQL and analytical techniques to validate requirements, support decision-making, and identify solution options.
Participate in Agile ceremonies, including backlog refinement, sprint planning, demonstrations, testing, release readiness, and retrospectives.
Manage risks, dependencies, and tradeoff decisions across stakeholders and delivery teams.
Prepare and deliver roadmap updates, prioritization recommendations, and product communications for leadership and stakeholder audiences.
Promote standardized data products, documentation, and consumption practices that improve discoverability, trust, and reuse.