at J.P. Morgan
Bulge Bracket Investment BanksPosted 13 days ago
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**Director of Data Engineering** at JPMorganChase in London leads data pipeline projects, driving impact across departments. Key responsibilities include leading teams to achieve functional tech objectives, making strategic decisions, carrying governance accountability, and delivering reusable data pipeline and architecture solutions. Required are formal data engineering training, experience leading cross-functional teams, working with enterprise AI tools, hiring and developing talent, and utilizing KDB. This senior role involves influencing stakeholders and serving as a primary decision-maker.
- Compensation
- Not specified
- City
- London
- Country
- United Kingdom
Currency: Not specified
Full Job Description
Location: LONDON, United Kingdom
You are poised to achieve extraordinary success and make a high impact on those around you. Partner with an organization comprised of the industrys thought leaders and committed to advancing your leadership career.
Job responsibilities
- Leads data and process implementation teams to achieve functional technology objectives
- Makes strategic decisions that influence teams resources, budget, tactical operations, and the implementation of processes and procedures
- Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
- Delivers data pipeline and architecture solutions that can be leveraged across multiple businesses
- Influences peer leaders and senior stakeholders across the business, product, and data technology teams
- Leads reuse-first adoption of enterprise-authorized AI capabilities within the work environment to accelerate data pipeline/architecture decisioning and delivery, with human-in-the-loop validation and appropriate handling of sensitive data.
- Establishes governance standards for AI-assisted workflows used in data engineering decision-making and delivery, ensuring traceability/auditability and alignment to resiliency, security, and control obligations.
Required qualifications, capabilities, and skills
- Formal training or certification on data engineering concepts and advanced applied experience
- Experience developing and/or leading cross-functional teams of technologists
- Demonstrated experience leading teams in the safe use of enterprise-authorized AI capabilities within the work environment for data engineering workflows, including validation habits and awareness of data sensitivity.
- Ability to evaluate AI-assisted recommendations before adoption and set review/approval expectations that align to resiliency, security, and auditability outcomes.
- Experience hiring, developing, and recognizing talent
- Experience leading a product as a Product Owner or Product Manager
- Experience with KDB
