Job Title: Data Product Owner - Wealth Management Reference Data
Work Location : NYC or Fort Mill, SC (Onsite Hybrid)
Contract duration: 12+ months Contract
Job Description
Data Product Owner – Reference Data, Security Master & Market Data (Wealth Management)
Mandatory skills
Hands on Data Analysis, Reference Data for Wealth Management
Domain: Wealth Management
Role Summary
We are seeking a highly independent Techno Functional Data Product Owner to lead Reference Data, Security Master, and Market Data for Wealth Management. This role spans instrument and issuer/entity data, security lifecycle, identifiers and symbology (CUSIP/ISIN/SEDOL/ticker), pricing and valuations, corporate actions, and market data vendor onboarding and controls. The role requires strong handson data analysis, deep understanding of wealth business processes, and the ability to translate requirements into implementationready technical deliverables with minimal supervision.
The role operates autonomously, owns outcomes end to end, and partners with trading, portfolio, operations, risk, compliance, and engineering teams to deliver accurate, wellgoverned reference and market data powering OMS/PMS, performance, risk, reporting, and digital channels.
Key Responsibilities
EndtoEnd Product Ownership
• Own Reference Data, Security Master, and Market Data requirements end to end
• Independently drive discovery, analysis, documentation, and backlog readiness
• Identify gaps, risks, survivorship conflicts, and data dependencies
• Own delivery outcomes, data quality, timeliness, and lineage
Reference Data, Security Master & Market Data Domain Ownership
• Lead goldencopy requirements across instrument, issuer/entity, pricing, and corporate actions
• Define identifier mapping, symbology crossreferences, and deduplication logic
• Own pricing and valuation sourcing, controls, and tolerance checks
• Establish authoritative SOR and multiSOR precedence, survivorship, and exception handling
• Ensure data products are reusable across trading, risk, reporting, and digital consumers
Stakeholder Collaboration & Requirement Elicitation
• Partner with business, operations, risk, compliance, 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 handson analysis of source systems, vendor feeds, and integrations
• 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 implementationready 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 data flows
• Define and enforce data quality controls, monitoring, and SLAs
• Partner with compliance and security on entitlements and licensing constraints
• Support auditability of onboarding and data changes
Data Contracts & Standards
• Own canonical data contracts covering definitions, schemas, code sets, and survivorship
• Define versioning and changemanagement 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 data
Required Skills & Experience
• 8+ years in Financial Services, preferably in Wealth Management data domains
• Strong technofunctional background spanning business, data, and technology
• Handson data analysis and fieldlevel validation experience
• Proven ability to write clear, implementationready Jira stories
• Working knowledge of event streaming, APIs, batch integrations, schemas, and data quality controls
• Selfstarter with strong ownership and accountability mindset
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