Data Product Owner (With Asset/Wealth/Investment Management)

Data Product Owner

Location: New York, NY

Employment Type: Full-Time

Work Model: Hybrid 3 Days Onsite

Position Overview

We are seeking a highly capable and self-driven Data Product Owner to join a Data & Technology organization supporting complex financial services and investment management functions.

This individual will serve as the bridge between business stakeholders and technical data engineering teams, owning the strategy, roadmap, and delivery of enterprise data products.

The ideal candidate is a seasoned, hands-on data professional with strong experience in financial services, preferably asset management, investment management, or wealth management. The role requires someone who can balance strategic product ownership with hands-on data analysis and execution.

Key Responsibilities

Product Ownership & Roadmap

• Own the end-to-end lifecycle of multiple enterprise data products, including Client Master, Transaction Master, Product Master, and other foundational datasets.
• Define, maintain, and communicate product roadmaps aligned with business priorities and enterprise data strategy.
• Manage product backlogs, user stories, acceptance criteria, and functional requirements.
• Define and track product KPIs, adoption metrics, and data quality benchmarks.
• Drive continuous product improvements based on stakeholder feedback and business outcomes.

Stakeholder Management & Requirements

• Partner with stakeholders across Sales, Finance, Operations, Enterprise Data, and Engineering teams.
• Conduct discovery sessions, workshops, and user interviews to identify business needs and pain points.
• Translate business requirements into clear and actionable product requirements for engineering teams.
• Manage stakeholder expectations, priorities, dependencies, and trade-offs.
• Prepare and present roadmap updates, business cases, and executive-level presentations.

Data Analysis & Quality

• Perform hands-on data analysis, including dataset profiling, anomaly identification, lineage validation, and accuracy checks.
• Define and maintain data quality standards, governance frameworks, and data dictionaries.
• Collaborate with Data Engineers and Architects to understand data models, pipelines, and platform infrastructure.
• Provide input into technical design decisions based on business and data requirements.
• Use AI and automation tools where appropriate to improve data analysis and product delivery efficiency.

Cross-Functional Collaboration

• Manage dependencies, risks, and blockers across multiple workstreams.
• Coordinate closely with business, product, data, and engineering teams.
• Evaluate data tools, platforms, and third-party vendors where required.
• Produce clear product documentation, executive summaries, and business cases.
• Drive accountability across business and technology teams to ensure successful delivery of data products.

Required Qualifications

• 8 10 years of experience in Data Product Management, Data Product Ownership, or a related data-focused role within Financial Services.
• Strong experience in Asset Management, Investment Management, or Wealth Management preferred.
• Proven experience owning and delivering multiple enterprise data products simultaneously.
• Strong hands-on experience with SQL and data analysis.
• Experience working with large and complex datasets across platforms such as Snowflake, Databricks, or equivalent.
• Strong understanding of:
• Data Governance
• Data Quality Management
• Metadata Management
• Data Lineage
• Master Data Management
• Experience managing product roadmaps, backlogs, user stories, and acceptance criteria.
• Experience with Agile tools such as Jira, Confluence, or equivalent.
• Excellent stakeholder management and communication skills.
• Ability to present complex data concepts clearly to senior and executive leadership.
• Highly organized and capable of managing multiple priorities independently.

Preferred Qualifications

• Experience with financial data domains such as:
• Portfolio and Position Data
• Investor Reporting
• AUM and Fund Flows
• Trade and Settlement Data
• Client Master Data
• Product Master Data
• Experience using Generative AI, LLM-based workflows, AI copilots, or AI-powered analytics tools.
• Experience evaluating and managing third-party data vendors.
• Strong understanding of enterprise data platforms and data transformation programs.