Role Summary
We are seeking a highly independent Techno Functional Data Product Owner to lead Advisor Data for Wealth Management. This role spans advisor and producer profile data, licensing and registration, book of business and household/relationship mapping, compensation and grid data, organizational/branch hierarchy, and advisor workstation and CRM data integration. The role requires strong hands-on data analysis, deep understanding of wealth business processes, and the ability to translate requirements into implementation-ready technical deliverables with minimal supervision.
The role operates autonomously, owns outcomes end to end, and partners with advisory/sales leadership, compliance, compensation, operations, risk, and engineering teams to deliver accurate, well-governed advisor data powering advisor workstations, CRM, compensation systems, compliance surveillance, and reporting.
Key Responsibilities
End to End Product Ownership
Own Advisor Data requirements end to end
Independently drive discovery, analysis, documentation, and backlog readiness
Identify gaps, risks, data conflicts, and dependencies across advisor systems
Own delivery outcomes, data quality, timeliness, and lineage
Advisor Data Domain Ownership
Lead golden copy requirements across advisor/producer profile, licensing and registration, and book of business data
Define identifier mapping (rep/producer IDs, CRD numbers, branch/region codes) and de-duplication logic
Own sourcing, controls, and validation for licensing, registration, and continuing education data
Establish authoritative SOR and multi-SOR precedence, survivorship, and exception handling across compliance and compensation systems
Ensure data products are reusable across advisor workstation, CRM, compensation, and compliance consumers
Stakeholder Collaboration & Requirement Elicitation
Partner with advisory/sales leadership, compliance, compensation, vendor management, and technology teams
Lead conversations on data needs, sourcing, usage, and required controls
Document and validate requirements, assumptions, decisions, and known unknowns
Data Analysis & Documentation
Perform hands-on analysis of source systems (licensing/registration platforms, CRM, compensation engines) and vendor feeds
Identify data gaps, overlaps, reuse opportunities, and quality failure patterns
Produce BRDs and data intake documents, attribute definitions, lineage flows, and NFRs
Partner with Data Governance and SOR teams on ownership, lineage, and standards
Agile Delivery & Backlog Management
Act as Product Owner for Agile delivery squads
Decompose requirements into epics, features, and implementation-ready Jira stories
Define inputs/outputs, events, schemas, quality rules, and change management
Own backlog prioritization, refinement, and sprint readiness
Integration, Kafka & API Ownership
Define delivery patterns using event streaming, APIs, and batch/file as appropriate
Collaborate on topic strategy, schemas, versioning, replay, and retention
Ensure scalability, reuse, and alignment to enterprise data standards
Governance, Risk & Controls
Embed metadata, lineage, auditability, and traceability across advisor data flows
Define and enforce data quality controls, monitoring, and SLAs
Partner with compliance on entitlements, licensing constraints, and regulatory recordkeeping
Support auditability of advisor onboarding, transfers, and data changes
Data Contracts & Standards
Own canonical data contracts covering definitions, schemas, code sets, and survivorship
Define versioning and change management standards
Maintain accurate and complete BRDs and intake documentation
AI Usage
Use AI responsibly to improve requirement quality and detect data quality patterns
Apply sound judgment with regulated, licensed, and sensitive advisor data
Required Skills & Experience
8+ years in Financial Services, preferably in Wealth Management advisor/producer data domains
Strong familiarity with Wealth Management business processes, advisor workflows, and industry data (licensing, registration, compensation, book of business)
Familiarity with advisor workstation platforms and their underlying data needs
Strong techno functional background spanning business, data, and technology
Hands-on experience working with data in a data team field-level data analysis, validation, and quality investigation
Proven ability to write clear, implementation-ready Jira stories
Working knowledge of event streaming, APIs, batch integrations, schemas, and data quality controls
Self-starter with strong ownership and accountability mindset
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