Data Product Owner - Manhattan, NY (Hybrid) - 12+ Months (Possible Extension)

Job Description

Job Description

Job Role             : Data Product Owner
Location             : Manhattan, NY (Hybrid)
Duration            : 12+ Months (Possible Extension) 
Job ID                 : 26-36384

Job Description:
Position Overview
Client is seeking a highly capable and self-driven Data Product Owner to join our data and technology team on a contract basis in New York. This 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.

Primary Responsibilities
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