Data Product Owner

Job Responsibilities

Mandate/Priority Requirements

• Strong Asset Management domain experience is mandatory
• Wealth Management experience is acceptable if the candidate has worked extensively with client/investor data and investment operations.
• Candidate must be willing to work 3-4 days/week from the New York office.
• Should work with business users, own data products end to end

Functional Expertise

• Experience owning or managing Client Master and Transaction Master data products.
• Strong understanding of investment data, investor/client onboarding, transactions, capital formation, investor reporting, fund operations, and related data domains.
• Hands-on experience with SQL, data profiling, data validation, reconciliation, data quality, and data analysis.
• Experience with Azure-based data platforms.

Product Ownership Expectations

• This is not a traditional Scrum Product Owner role, this is a Data Product Owner Role
• Candidate should be able to:
• Work directly with business users and understand data needs.
• Define requirements and translate them into engineering deliverables.
• Participate in build validation and UAT/testing activities.
• Drive stakeholder adoption and champion the data product.
• Coordinate end-to-end delivery across business and technology teams.

Candidates from below companies:

Blackstone, KKR, UBS, Merylinch , Ares, Carlyle, Brookfield, Blue Owl, BlackRock, Fidelity, Wellington, Franklin Templeton and similar investment firms

8–10 years of experience in data product management, data product ownership, or a closely related data-focused role within financial services; background in investment management or wealth management is strongly preferred

Proven track record of owning and delivering multiple data products simultaneously, including full roadmap ownership and end-to-end management of data transformation programs

Strong hands-on proficiency with data analysis and querying

Demonstrated experience managing large, complex datasets across enterprise data platforms (e.g., Snowflake, Databricks, or equivalent)

Working knowledge of data governance principles, data quality management, metadata management, and data lineage practices

Excellent communication skills—written, verbal, and visual—with the ability to translate complex data concepts into clear business language and present confidently to senior and executive leadership

Highly organized and detail-oriented; able to manage competing priorities independently, hold high personal standards, and deliver quality work with minimal supervision

Proficiency with product and project management tools such as Jira, Confluence, or equivalent

Preferred

Direct domain expertise in asset management or wealth management data (e.g., portfolio and position data, investor reporting, AUM and flows, trade and settlement data)

Demonstrated experience leveraging AI tools—including generative AI assistants, LLM-based workflows, or AI-powered analytics platforms—to accelerate data product development and analysis

Experience evaluating and managing third-party data vendors