Lead Data Engineer: AI-Ready Data & Governance

Fairygodboss; Greater London; On-site; GBP 110,000 - 150,000; Full time

Job summary

J.P. Morgan is seeking a Lead Data Engineer to join the Chief Data and Analytics Office of Asset & Wealth Management. You will drive data provisioning and governance at scale, partnering with business, technology, and operations to deliver AI-ready data assets that enable trusted insights and regulatory compliance.

You will lead data quality initiatives, develop lineage reporting, and empower executives with dashboards and metrics while advancing mesh data architectures and metadata enrichment.

Qualifications

• Formal training or certification on data engineering concepts.
• Deep subject matter expertise in wealth and asset management data domains, including customer, account, position, transaction, and/or reference data.
• Proven ability to deliver results in a matrixed and complex environment, with demonstrated experience influencing stakeholders at all levels of an organization.
• Experience leading strategic or transformational data initiatives, including data governance, data quality programs, or analytics transformation.
• Strong technical proficiency in data profiling, analysis, and data management using modern tools and environments, including Python, R, SQL, Spark, and cloud platforms.
• Experience with data quality frameworks, including profiling, rule development, issue remediation, and the design of preventative controls.
• Ability to translate complex technical findings into clear executive-level communications, dashboards, and performance reporting.

Responsibilities

• Provision new and differentiated data assets to support AI and analytics initiatives, partnering with use case owners to define requirements, manage product dependencies, and accelerate delivery through AI-enabled data tooling
• Drive executive visibility into the progress of making critical data sources available, including performance metrics, adoption tracking, and transparency into bottlenecks
• Support agile product routines to oversee cross-product data dependencies, prioritize delivery, and align resources across business, technology, and operations partners
• Identify and document the lineage and provenance of critical data assets to support governance, regulatory, and business requirements, embedding evergreen controls to improve safety and traceability
• Develop and deliver data lineage analysis and reporting that provides executive visibility on progress against critical service-level agreements, including blockers and resourcing needs
• Lead root cause analysis of data quality issues using deep data profiling and advanced analytics techniques, fixing identified issues and embedding preventative controls to reduce future failures
• Drive operational efficiency by eliminating the cost of poor data quality through common tooling, frameworks, and proactive control development
• Enrich the metadata and semantic layer of existing data assets to improve discoverability, usability, and value for AI applications and natural language query capabilities
• Accelerate adoption of mesh data architecture by uplifting existing data assets with improved metadata, data quality scores, and lineage information
• Develop and deliver data product prototypes that demonstrate the value of enriched data assets and reduce consumer friction caused by incomplete documentation or poor catalogue quality

Skills

Python

SQL

Spark

R

Cloud platforms

Data governance

Data quality

Stakeholder management

Executive communication

Analytical thinking

Education

Bachelor's degree in CS/Engineering/IT

Data engineering certification

Tools

Graph databases

Metadata management platforms

Tableau

Power BI

Git

GitHub

Bitbucket

Job description

J.P. Morgan is seeking a Lead Data Engineer to join the Chief Data and Analytics Office of Asset & Wealth Management. You will drive data provisioning and governance at scale, partnering with business, technology, and operations to deliver AI-ready data assets that enable trusted insights and regulatory compliance.

You will lead data quality initiatives, develop lineage reporting, and empower executives with dashboards and metrics while advancing mesh data architectures and metadata enrichment.