Director of Data Engineering

You are poised to achieve extraordinary success and make a high impact on those around you. Partner with an organization comprised of the industry’s thought leaders and committed to advancing your leadership career. 
 

As a Director of Data Engineering at JPMorganChase within the Macro space you lead a data pipeline and drive impact within teams, technologies, and projects across departments. Utilize your in-depth knowledge of data, analytics, applications, technical processes, and product management to lead multiple complex projects and initiatives, make key decisions for your team, and a drive innovation and solution delivery. 

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