Asset Management - Data Owner - Vice President

JPMorgan Chase & Co.; Greater London; On-site; GBP 110,000 - 150,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a data product owner for a mission-critical data platform in London. You will own the product vision and execution for data services powering client reporting, workflows and investment processes, while advancing AI-enabled automation and data quality engineering.

The role requires a builder mindset, comfort with ambiguity, and a track record of delivering durable data products that drive adoption and measurable value across the firm.

Qualifications

• Proven track record in data management across governance, lineage, metadata and quality controls.
• At least 10 years of Financial Services experience blending data, tech and operations knowledge.
• Delivered in agile environments with backlog discipline and outcome-based execution.
• Comfortable navigating large datasets with SQL and/or Python to validate hypotheses.

Responsibilities

• Own end-to-end delivery for a critical data domain, aligning with business priorities and measurable value.
• Lead governance, domain boundaries, and AI readiness for data products.
• Translate complex needs into problem statements, use cases, and success metrics for delivery teams.
• Design a modernization roadmap spanning data platform evolution, quality tooling and metadata enablement.
• Identify and implement AI opportunities while ensuring safety, explainability, and governability.
• Collaborate with Business, Operations, Technology and Controls to accelerate delivery and remove blockers.
• Manage dependencies across teams and release trains for predictable outcomes.
• Define and track delivery and outcome metrics to refine the roadmap.

Skills

Data management

10+ years FS data experience

Agile delivery

SQL

Python

AI product fluency

Stakeholder influence

Communication

Tools

SQL

Python

Job description

Join our team to build and scale 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.

Job Summary

As a data owneron 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

Job responsibilities

• 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 opportunitiesincreasing 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.

Required qualifications, capabilities, and skills

• 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)