Data Product Owner

Data Product Owner – Advisor Data

Industry: Financial Services / Wealth Management

Experience: 8+ Years Focus: Advisor Data | Data Product Ownership | Wealth Management | Data Analysis | Agile/Jira | APIs/Kafka

Position Overview: We are seeking an experienced Data Product Owner – Advisor Data to lead critical data initiatives within a Wealth Management organization. This is a highly autonomous, techno-functional role requiring someone who understands Wealth Management from both a business and data perspective. The ideal candidate has direct experience with advisor/producer data and can work hands-on with data while translating complex business requirements into implementation-ready deliverables for engineering teams. This is not a traditional Product Owner role focused primarily on backlog administration. Candidates should have meaningful Wealth Management domain expertise and be comfortable investigating data at the field level.

What You'll Own:

• Lead Advisor Data requirements and delivery from discovery through implementation.
• Own data associated with: Advisor and producer profiles Licensing and registration Book of business Household and relationship mapping Compensation and grid data Branch and organizational hierarchies Advisor workstation and CRM integrations
• Establish golden-copy requirements, authoritative systems of record, source precedence, survivorship rules, and exception handling.
• Define identifier mapping across rep/producer IDs, CRD numbers, branch codes, and related identifiers.
• Identify data conflicts, duplication, quality issues, dependencies, and gaps across advisor systems.
• Own data quality, lineage, timeliness, controls, and delivery outcomes.

Hands-On Data Analysis: This role requires someone comfortable getting into the data—not simply gathering requirements. You will:

• Analyze source-system and vendor-feed data at the field and attribute level.
• Investigate data-quality failures and discrepancies.
• Perform validation and reconciliation.
• Analyze CRM, licensing/registration, compensation, and related advisor data.
• Define attribute definitions, lineage, business rules, and data-quality controls.
• Partner with Data Governance teams on ownership, standards, metadata, and lineage.

Product Ownership & Agile Delivery: Serve as Product Owner for Agile data-delivery squads. Translate business requirements into epics, features, and implementation-ready Jira stories. Define inputs, outputs, schemas, events, quality rules, acceptance criteria, and non-functional requirements. Own backlog prioritization, refinement, and sprint readiness. Produce BRDs, data-intake documentation, lineage flows, and supporting requirements documentation.

Integration & Data Architecture: Partner with engineering and architecture teams to define appropriate delivery patterns across: Kafka / event streaming APIs Batch and file integrations Data schemas and contracts Topic strategy and versioning Replay and retention Data-quality monitoring Change management The Product Owner will also establish canonical data contracts covering definitions, schemas, code sets, survivorship, and versioning.

Stakeholder Partnership: Work across a broad Wealth Management stakeholder community, including: Advisory and Sales leadership Compliance Compensation Operations Risk Data Governance Engineering and Architecture Vendor Management The successful candidate must be capable of independently leading discovery conversations, challenging assumptions, identifying unknowns, and driving decisions.

Required Qualifications: 8+ years of Financial Services experience, with Wealth Management strongly preferred. Strong knowledge of advisor/producer data and Wealth Management business processes. Experience with advisor data including licensing, registration, compensation, book of business, and organizational structures. Understanding of advisor workflows and advisor workstation/CRM data requirements. Strong techno-functional background spanning business, data, and technology. Hands-on data analysis experience, including field-level analysis, validation, reconciliation, and data-quality investigation. Proven ability to create clear, technically actionable Jira stories and requirements. Working knowledge of Kafka/event streaming, APIs, batch integrations, schemas, and data-quality controls. Strong stakeholder management and requirements-gathering capabilities. Ability to operate independently with significant ownership and accountability.