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# Asset Management - Data Owner - Vice President

- **Company:** JPMorgan Chase & Co.
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Big Data, Data as a Services, Data Infrastructure, Distributed Computing Environment, Python (Programming Language), SQL Databases, GitHub Copilot, Agentic-AI, Data Management
- **Published:** October 9, 2026
- **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210798454

## About the Role

* Proven track record in data management: system-of-record, lineage, metadata, data quality, controls, stewardship, and lifecycle management.
 * At least 10 years of Financial Services experience, with data, technology and operations experience blended with knowledge of Asset& Wealth Management data concepts
 * Delivered in agile environments with real backlog discipline, pragmatic scope control, and outcome-based execution
 * Comfortable with SQL and/or Python, navigating large datasets to validate hypotheses, investigate issues, and partner credibly with engineering and analytics
 * Practical fluency with AI and Agentic AI for data products: automated reconciliations, anomaly detection, data-issue triage, metadata enrichment, exception handling, and workflow orchestration
 * Able to evaluate AI honestly - value, risk, scalability, control points, operational readiness - and turn experimentation into production outcomes
 * Influence stakeholders at every level, aligning diverse groups around clear priorities and standards
 * Excellent written and verbal communication, including materials sharp enough for governance forums and senior leadership.

Preferred qualifications, capabilities, and skills

 * Hands-on with foundational AI tooling - VS Code, GitHub Copilot - and the modern developer environment
 * Hands-on with data-quality tooling, metadata platforms, lineage frameworks, and modern data platforms (lakehouse/warehouse patterns, distributed processing, APIs/data services)

## Description

As a data owner on a mission-critical data product, you'll own the product vision and execution for many efforts, including the data services that power client reporting, operational workflows, and investment processes-while pushing the frontier on AI-enabled automation, Agentic AI readiness, and modern data quality engineering. This role is for a builder who thrives in ambiguity, moves with agility and sharp judgment, and turns complex, high-stakes data problems into durable products that teams actually adopt. If you want a long runway, real impact, and a front-row seat to how AI reshapes enterprise data, this is your seat, * Own delivery end-to-end for a critical data domain-intake through outcomes-ensuring delivery aligns to business priorities and measurable client/user value.

 * Run the full data ownership agenda: governance and controls, domain boundaries, downstream consumption from systems-of-record, retention & destruction and AI readiness.
 * Translate complex needs into crisp product direction: define problem statements, use cases, success metrics, user journeys, and acceptance criteria that enable delivery teams to move quickly without losing rigor.
 * Design and drive a modernization roadmap spanning data platform evolution, quality tooling, metadata/lineage enablement, and scalable operational processes.
 * Identify and implement AI opportunities increasing straight-through processing, and improving data quality-while ensuring solutions are safe, explainable, and governable.
 * Drive execution with cross-functional partners across Business, Operations, Technology, and Controls-removing blockers, establishing operating models, clarifying decisions, and accelerating delivery.
 * Manage dependencies and sequencing across teams, platforms, and release trains to ensure predictable, high-quality outcomes.
 * Measure what matters: establish and maintain delivery and outcome metrics (quality, timeliness, adoption, STP lift, defect reduction, cycle time) and use them to refine the roadmap.