Executive Director – Head of Asset Management Operations, Data Strategy

JPMorgan Chase & Co.; Greater London; On-site; GBP 120,000 - 160,000; Full time

Job summary

A leading global financial services firm in the UK is seeking an Executive Director and Head of Asset Management Operations to drive innovative data strategies. This role requires expertise in fund accounting and investment accounting to ensure data integrity. Responsibilities include defining data architecture, managing data domains, and promoting a data-driven culture. Strong leadership ability, excellent communication skills, and experience in Agile methodologies are essential. Join this influential role to shape the future of data management.

Qualifications

• Bachelor’s degree with industry experience in a data‑related role.
• Expertise in position, transaction, performance, and attribution data domains.
• Strong familiarity with advanced analytics, machine learning, and AI applications.

Responsibilities

• Define target data architecture and maintain scope for data domains.
• Design scalable data architecture that meets business requirements.
• Manage all data domain artifacts and lead a team of Data Owners.

Skills

Experience in fund accounting

Investment accounting

Data management

Agile methodologies

Leadership skills

Education

Bachelor's degree

Tools

Data management tooling

Cloud-based data platforms

Job description

Shape the future of Asset Management with visionary data leadership. As the Executive Director and Head of Asset Management (AM) Operations, Data Strategy, you’ll shape and execute a cutting‑edge approach to data development, governance, and delivery—empowering business growth, operational excellence, and advanced analytics.

In this role, you will leverage your expertise infund accounting, investment accounting, and accounting principlesto ensure data integrity and compliance across all operational processes. You will ensure that data inputs, outputs, and impacts are well understood and optimized for key consumers, including portfolio managers, investment specialists, client service teams, and other operations stakeholders.

Join us today to transform data into a strategic asset at the heart of our operations!

Job Responsibilities

• Partner with the Asset & Wealth Management (AWM) Chief Data Officer to define target data architecture and maintain scope for position, transaction, performance, and attribution data domains, ensuring alignment with Asset Management’s data strategy.
• Collaborate with business process owners and Technology architects to design scalable, flexible data architecture that meets business and accounting requirements.
• Own the data landscape for these domains, including migration planning from legacy to strategic systems of record.
• Identify and govern Critical Data Elements (CDEs), ensuring regulatory compliance, data lineage, and adherence to accounting standards.
• Manage all data domain artifacts (data dictionary, quality rules, lineage documentation) and lead a team of AM Operations Data Owners for their maintenance and enhancement.
• Govern and evolve the data domain structure through participation in the Data Architecture Council and decision‑making on domain changes.
• Promote data literacy and a data‑driven culture across domains and all key Product, Operations, and Technology partners while ensuring robust data management practices and operating models in partnership with AM Operations leadership.
• Collaborate with other Data Owners to ensure data integration, integrity, secure access, and enforcement of domain boundaries, especially for accounting and performance data.
• Own and enforce data contracts, ensuring clear standards for data quality, accessibility, and usage between producers and consumers.
• Lead engagement with data producers, consumers, and reporting/BI/data science communities to understand requirements, prioritize initiatives, and drive adoption of data products and enhancements.
• Oversee data risk metrics, compliance, and governance through participation in relevant councils, and direct Product Owners to uplift data quality, manage retention/destruction, and ensure security, confidentiality, and regulatory compliance.

Required qualifications, capabilities, and skills

• Bachelor’s degree with demonstrable industry experience in a data‑related role, with experience infund accounting, investment accounting, and accounting principles.
• Subject matter expertise in position, transaction, performance, and attribution data domains within an Asset Management ecosystem.
• Experience managing delivery across multiple workstreams with varying timelines, priorities, and complexities, especially in accounting, performance, and operations environments.
• Demonstrated ability to manage tight delivery timelines and ensure the product and organization are on track to execute and deliver strategic changes that meet goals.
• Ability to execute via successful internal partnerships with other organizations, with the ability to influence people at all levels across a broad variety of job functions.
• Excellent leadership skills in managing products, programs, projects, and teams.
• Structured thinker and effective communicator with excellent written communication skills.
• Ability to crisply articulate complex technical, performance, and accounting concepts simply to senior audiences with poise and confidence.
• Technical understanding of data management and governance, cloud‑based data platforms, or data architecture.
• Understanding of product development and Agile methodologies, with experience in product management focused on data products and data‑driven decision‑making.

Preferred qualifications, capabilities, and skills

• Strong familiarity with data management tooling (e.g., quality, observability, discovery, profiling).
• Experience with regulatory reporting and compliance in Asset Management Operations.
• Experience supporting data needs and impacts for portfolio managers, investment specialists, client service, and operations stakeholders.
• Strong familiarity with advanced analytics, machine learning, and AI applications in a business context.
• Demonstrated experience with cloud‑based data platforms and technologies (e.g., AWS, Azure, Google Cloud).