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

LPL Financial Global Capability Center

Hyderabad, INhybridPosted Jun 18, 2026

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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