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Data Owner Lead - Data Management Operations - Vice President
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JPMorgan Chase Bank, N.A.
Jersey City, NJ (In Person)
Full-Time
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Job Description
Join the Chief Administrative Office - Chief Data & Analytics Office and help shape the future of data management at JPMorganChase. As a Data Owner Lead, you will drive impactful data strategies and foster a data-driven culture. This role offers opportunities for career growth, skill development, and collaboration with industry-leading experts. Be part of a team that leverages AI and machine learning to support the firm's commercial goals. In addition to strong governance execution, this role emphasizes hands-on data product delivery-bringing data together from multiple sources, shaping it into high-quality, reusable data products, and enabling broad consumer populations and advanced analytical solutions. As a Data Owner Lead within the Chief Data & Analytics Office, you will execute data strategies that align with business operations and strategic objectives. You will collaborate with cross-functional teams to ensure data is understood, fit for purpose, and well-governed. You will also partner with Technology and Analytics to define and maintain data products, including curation, semantic consistency, documentation, and lifecycle management. In this role, you will help drive organizational growth and competitive advantage by supporting a culture of data-driven decision-making. You will work closely with partners across Business, Technology, Analytics, Operations, and Risk and Control functions. Your leadership will ensure data quality, integrity, and security, while supporting innovation and compliance with data governance standards. You will partner with information architecture and data platform teams to ensure data products are scalable, discoverable, and fit for enterprise use. Job Responsibilities
- Implement strategic plans to deliver data solutions and data products that support business operations and strategic objectives.
- Manage project execution, mitigating risks and inefficiencies.
- Collaborate with partners to document and classify critical data with metadata. Ensure metadata is actionable and supports discovery and reuse (business definitions, technical metadata, lineage, quality rules/thresholds, and product documentation).
- Provide subject matter expertise on data content and usage within the business and associated product areas.
- Develop relationships with data providers and consumers across multiple functions. Engage broad-based consumer populations (operations, reporting, analytics, data science) to understand usage patterns and improve usability of curated datasets and data products.
- Document requirements for data sourcing, content, and quality. Define requirements for integrating multiple upstream sources (including mapping, transformation logic, and reconciliation) and for building curated datasets that support analytics and reporting use cases.
- Develop processes to identify and mitigate data risks throughout the data lifecycle, including data protection, privacy, retention,.