Data Product Manager - Associate

Unleash your expertise in product development and optimization by leveraging user research, analyzing metrics, and collaborating across one of the world’s most innovative financial organizations.

As an Associate Data Product Manager in the Talent Data Product team, you will contribute to the team by leveraging your expertise in product development and optimization to make a significant impact, supported by user research and customer feedback to fuel the creation of innovative products and continuously improve existing offerings. Collaborate closely with cross-functional teams and play a crucial role in shaping the future of our products and ongoing success. . In this role, you will help execute the roadmap for data products that support Talent Acquisition, Onboarding, Off‑boarding, and Workforce Planning. You will partner across Business Intelligence, AI/ML, Product, Information Architecture, and Data Engineering to deliver curated, high‑quality, well‑governed datasets that enable a cohesive, frictionless, and personalized candidate and employee experience. This is an execution‑oriented role with clear ownership of discovery, requirements, backlog, delivery coordination, and data product quality.

Job responsibilities

• Partners with the Product Manager to identify new product opportunities that reflect the needs of our customers and the market through user research and discovery
• Considers and plans for upstream and downstream implications of new product features on the overall product experience
• Supports the collection of user research, journey mapping, and market analysis to inform the strategic product roadmap and provide insight on potential product features that provide value to customers
• Analyzes, tracks, and evaluates product metrics including work to time, cost, and quality targets across the product development life cycle
• Writes the requirements, epics, and user stories to support product development 
• Conduct user discovery and stakeholder interviews to gather business requirements, pain points, and opportunities for improvement. 
• Partner with Business Intelligence, AI/ML, and Product teams to ensure data products meet reporting, analytics, and automation needs. 
• Collaborate with Information Architecture and Data Engineering to onboard new data sources and transform them into performant, fit-for-purpose data offerings. 
• Establish and maintain strong data governance, quality, and lifecycle management practices for talent data, ensuring compliance with firmwide standards. 
• Own the development and maintenance of data catalog, metadata, glossary, and lineage capabilities for Talent Acquisition and Off-boarding datasets. 
• Drive continuous improvement in data product offerings through stakeholder feedback, usage insights, and industry best practices. 

Required qualifications, capabilities, and skills

• 2+ years of experience or equivalent expertise in product management or a relevant domain area
• Proficient knowledge of the product development life cycle
• Experience in product life cycle activities including discovery and requirements definition
• Developing knowledge of data analytics and data management. 
• Translate business needs into epics, features, and user stories with clear acceptance criteria; maintain a transparent, prioritized backlog and delivery plan.
• Proficiency in SQL for data testing, validation, and ad‑hoc analysis; ability to guide users on how to access and use data products effectively.
• Strong stakeholder engagement and communication skills; ability to translate technical capabilities into clear business outcomes and articulate trade‑offs.

Preferred qualifications, capabilities, and skills

• Understanding of privacy and compliance considerations related to HR data.
• Experience with data onboarding, metadata management, governance workflows, and compliance in control‑heavy or regulated environments with multiple lines of defense.

• Working knowledge of modern data platforms and cloud ecosystems, including entitlements, catalog, lineage, and data quality tooling

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