AVP, Data Product Owner – Wealth Management (Data Products)
About the role
At LPL’s Global Capability Center, you'll find a collaborative culture where your voice matters, integrity guides every decision, and technology fuels progress. Your skills, talents, and ideas will redefine what's possible. LPL's success reflects its exceptional employees, who together pursue one noble purpose: empowering financial advisors to deliver personalized advice for all who need it. We’re proud to be expanding and reaching new heights in Hyderabad.
Join us as we create something extraordinary together.
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
LPL Global Business Services, LLP - PRIVACY POLICY
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