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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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As a Data Product Manager – Vice President within the Firmwide Financial Control team, you will safeguard the integrity of firm books and records while defining global target platform strategies to modernize operations at scale. You will partner with stakeholders to drive product discovery, manage a prioritized backlog, and translate complex data requirements into technical specifications across the software development life cycle. Your daily work involves ensuring data is structured for reuse through logical and physical modeling, establishing quality controls, and preparing data for AI/ML capabilities like anomaly flagging. You must possess expertise in data governance, SQL, and large dataset analysis. The role addresses critical financial control challenges within a regulated environment, utilizing modern architecture concepts such as batch processing, APIs, and data contracts to deliver trusted outcomes through structured data models and automated reporting solutions.
Gather and refine requirements from stakeholders to define product scope and use cases.
Manage a prioritized product backlog and roadmap to ensure the delivery of key capabilities.
Translate business requirements into technical design principles and acceptance criteria for development teams.
Oversee data modeling, sourcing, and contract definition to ensure structured data is built for scale.
Define and implement data quality rules and controls to ensure information is accurate and trustworthy.
Prepare and position data assets to be AI-ready for anomaly flagging and trend surfacing.
Bridge the gap between technical delivery and business needs across the software development lifecycle.
What we're looking for
7+ years of experience in data product management, data governance, financial data delivery, or analytics solutions within a regulated industry.
Demonstrated experience delivering outcomes across multi-stakeholder workstreams including intake, prioritization, dependency management, and risk reporting.
Working knowledge of modern data architecture concepts such as logical/physical modeling, batch/streaming, APIs, lineage, and data contracts.
Strong command of data governance and controls, including lifecycle practices, cataloging, quality controls, and security access controls.
Proficiency with data and analytics tooling, including SQL, to work with large, complex datasets for validation and reporting.
Strong stakeholder management skills to translate between technical and business perspectives and drive adoption.
Experience in Finance, Financial Control, Risk, or Treasury within a matrixed, regulated organization (preferred).
Familiarity with modern data platforms (AWS, Databricks, Snowflake), AI/ML integration, Agile environments, and Python (preferred).
Data Management
AI
Generative AI
Data Quality
Contract Lifecycle Management
Data Governance
Agile
Data Analytics
Data Architecture
Data Integration
AWS
Informatica
Collibra
Talend
Cloud Platforms
Data Product Management
Data Governance
Data Architecture
Warehouse
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Business Intelligence
Backlog Management
Data Quality
Analytics
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Generative AI
Agentic AI
RAG
Knowledge Graphs
Ontology
Semantic Engineering
Data Management
Metadata Management
Agile
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Context Engineering
Data Governance
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SQL
Data Governance
Data Engineering
Data Catalog
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Data Quality
User Stories
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