Lead Engineer - Data / Java / Python

JPMorgan Chase & Co.; Glasgow; On-site; GBP 90,000 - 130,000; Full time

Job summary

JPMorganChase within Finance Technology seeks a Lead Software Engineer to join an agile team delivering secure, scalable technology products that support the firm's objectives.

You will guide architectural decisions, drive AI-assisted engineering practices, and contribute across frontend, backend, data pipelines, and mobile areas to raise code quality and delivery speed.

Qualifications

• Formal training or certification on software engineering concepts and advanced applied experience.
• Strong fundamentals in system design, data structures, algorithms, and architectural thinking.
• Experience across full-stack or cross-functional development with frontend, backend, data pipelines, or mobile.
• Proficiency in Java/Spring Boot, Python/PySpark, GraphQL or mobile frameworks with willingness to learn others.
• Experience with cloud platforms (preferably AWS) and relational and distributed data platforms.

Responsibilities

• Execute creative software solutions, design, development, and debugging with non-routine problem solving.
• Develop secure, high-quality production code and review code written by others.
• Identify opportunities to automate remediation to improve stability of applications.
• Lead evaluation sessions with vendors and internal teams on architecture and feasibility.
• Lead communities of practice to promote new technologies and best practices.
• Drive adoption of AI-assisted engineering practices to improve code quality and delivery speed.
• Apply SDLC tools and AI-assisted development capabilities to enhance value and reuse.

Skills

System design

Data structures

Algorithms

Architectural thinking

Full-stack development

Java/Spring Boot

Python/PySpark

AWS

CI/CD

Secure coding

Tools

Java/Spring Boot

Python/PySpark

GraphQL

AWS

Oracle

Job description

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

As a Lead Software Engineer at JPMorganChase within Finance Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job Responsibilities

• Execute creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develop secure high-quality production code, and review and debug code written by others
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Add to team culture of diversity, opportunity, inclusion, and respect
• Drive team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and advanced applied experience
  Strong software engineering fundamentals — system design, data structures, algorithms, and architectural thinking — with the ability to ramp up quickly across varied tech stacks and project types
• Hands-on practical experience in full-stack or cross-functional development, spanning frontend, backend, data pipelines, or mobile, with demonstrated ability to contribute across the length and breadth of a project
• Proficiency in one or more of the following: Java/Spring Boot, Python/PySpark, GraphQL, or mobile development frameworks, with openness and aptitude to work across others as needed
• Experience with cloud platforms (preferably AWS) and working knowledge of both relational and distributed data platforms (e.g., Oracle, Databricks)
• Advanced understanding of agile methodologies, CI/CD pipelines, application resiliency, and secure software development practices
• Proficient in all aspects of the Software Development Life Cycle, including design, development, testing, and operational stability in production environments
• Practical understanding of AI/ML concepts and experience integrating or embedding AI/ML capabilities into business applications or data workflows, with the ability to identify opportunities where intelligent automation or predictive solutions can add business value
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
• In-depth knowledge of the financial services industry and their IT systems

Preferred qualifications, capabilities, and skills

• Experience with high-volume batch and real-time data processing using PySpark or similar frameworks, including performance tuning and troubleshooting of large-scale data pipelines
• In-depth knowledge of relational and distributed databases (e.g., Oracle, Databricks) with hands-on experience in query optimization, PL/SQL, and shell scripting in a cloud-native AWS environment
• Demonstrated ability to lead or contribute to architectural design discussions, technical evaluations, and proof-of-concept initiatives across diverse technology domains
• Experience working in or alongside financial services technology teams, with an understanding of regulatory, compliance, and security considerations in enterprise-grade systems