Data Product Owner
Location : NY-based (minimum 3 days per week in the office)- local only
Must have strong/extensive Wealth Management or Asset Management domain experience
Role: Data Product Owner | Location: New York, NY | Department: CFXP
The individual will serve as the bridge between business stakeholders and technical data engineering teams, owning the strategy, roadmap, and delivery of client data products that power critical client-facing and investment management functions across the firm.
The ideal candidate is a seasoned, hands-on data professional with deep roots in financial services—particularly asset management or wealth management—who can hit the ground running and contribute immediately at a high level. This person thrives in a fast-paced environment, exercises strong judgment, and balances strategic thinking with meticulous execution. They are as comfortable writing a SQL query to validate a dataset as they are presenting a product roadmap to senior leadership.
Product Ownership & Roadmap
- Own the end-to-end product lifecycle for multiple enterprise data products simultaneously—including core data assets such as Client Master, Transaction Master, Product Master, and other foundational datasets—from ideation through delivery and continuous improvement
- Define, maintain, and communicate a prioritized product roadmap aligned to business objectives and the firm's broader data strategy
- Develop and manage detailed product backlogs; author clear, actionable user stories, acceptance criteria, and functional specifications
- Define and track product KPIs, adoption metrics, and data quality benchmarks; iterate on products based on outcomes and user feedback
Stakeholder Engagement & Requirements
- Partner closely with stakeholders across Sales & Strategy, Finance, Operations, the Enterprise Data Office, and Engineering to surface data needs and translate them into well-scoped product requirements
- Conduct structured discovery sessions, workshops, and user interviews to understand pain points and define the right problem before designing solutions
- Serve as the primary liaison between business users and data engineering teams, ensuring requirements are unambiguous and delivered solutions meet user expectations
- Proactively manage stakeholder expectations, communicate trade-offs clearly, and build trusted, long-term relationships at all organizational levels
- Prepare and present executive-level updates, roadmap reviews, and business cases to senior leadership and key decision-makers
Data Analysis & Quality
- Perform hands-on data analysis—including dataset profiling, anomaly identification, lineage validation, and accuracy checks—across large and complex financial datasets
- Define and enforce data quality standards, governance frameworks, and data dictionaries for owned products
- Collaborate with data engineers and architects to understand underlying data models, pipelines, and platform infrastructure; provide informed input into technical design decisions
- Leverage AI and automation tools to accelerate data analysis, surface insights, and improve product delivery velocity
- Champion data literacy across business teams; help users understand, trust, and effectively use data products
Cross-Functional Collaboration
- Manage dependencies, risks, and blockers across workstreams; escalate issues proactively with recommended resolution paths
- Evaluate and recommend data tools, platforms, and vendors in support of product and technology strategy; manage vendor relationships where applicable
- Produce clear, audience-appropriate documentation, executive summaries, and business cases to support decisions and secure organizational alignment
- Foster a collaborative, outcome-oriented culture across business and technology teams, driving shared accountability for data product success
Qualifications & Experience
Required
- 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
Regards
Ravi Sharma
Never miss an opportunity! Create an alert based on the job you applied for.
