Director of Software Engineering Big Data, Cloud

We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.

As a Director of Software Engineeringat JPMorgan Chase within Corporate Technology you lead a technical area and drive impact within teams technologies and projects across departments. Utilize your in-depth knowledge of software applications technical processes and product management to drive multiple complex projects and initiatives while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.

Job responsibilities

• Leads the delivery of Trade Surveillance solutions aligned with business goals and regulatory requirements
• Drives the platform modernization initiative leveraging Data Mesh principles on Databricks to build scalable resilient and efficient big data platforms
• Provides hands-on technical leadership and guidance to engineering teams ensuring engineering excellence secure-by-design and agile/DevOps best practices
• Manages multiple feature teams acting as both a people supervisor and technical leader; hire develop mentor and recognise talent across cross-functional teams
• Owns decisions on team resources budgets and tactical operations including process execution and continuous optimisation.
• Evaluates selects and integrates emerging technologiesincluding AI/ML solutionsto enhance surveillance coverage accuracy efficiency and also leads and drives AI projects fostering AI readiness and adoption with the global team.
• Builds and nurture a collaborative environment that encourages innovation and continuous improvement.
• Identifies and mitigate risks across data models security and operations; ensure audit readiness and control compliance.
• Develops strong partnerships with product compliance and LOB Technology also drives transformation and modernisation projects to achieve shared objectives.
• Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed quality and operational outcomes (e.g. AI-orchestrated delivery workflows release readiness controls automated test modernisation and incident triage acceleration) while establishing guardrails for validation security resiliency traceability and reuse across teams
• Applies knowledge of tools within the Software Development Life Cycle toolchain including enterprise-authorized AI-assisted development and automation capabilities to improve the value realised by automation and support capacity unlock initiatives at scale

Required qualifications capabilities and skills

• Solid track record and 10 years of experience in building large-scale data warehouses enterprise data platforms and critical big data solutions
• Proven experience in cloud implementation and practical cloud-native development with AWS Azure or GCP
• Deep expertise in platform building modernization and transformation projects including Data Mesh and Databricks
• Familiarity with AI/ML technologies and experience leading or driving AI projects
• Experience developing or leading cross-functional teams of technologists including hiring developing and recognising talent
• Strong people management skills; ability to supervise mentor and grow engineering leaders and teams
• Excellent communication collaboration and stakeholder management skills
• Ability to drive innovation and foster a culture of continuous improvement
• Experience managing multiple Scrum/feature teams and delivering complex projects in an agile environment
• Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorised tools within the work environment) across teams including defining operating expectations (human-in-the-loop validation quality gates) measuring outcomes and ensuring secure handling of sensitive inputs/outputs
• Strong understanding of responsible AI use and control expectations in engineering workflows including data sensitivity resiliency/security implications and governance; ability to influence leaders on safe scaling patterns and reuse

Preferred qualifications capabilities and skills

• Experience working at code level