Lead Java Engineer

You’ll work on foundational capabilities used by multiple delivery teams, helping create reliable, scalable and reusable solutions across API, batch and event-driven processing. This is a role for someone who enjoys solving complex engineering problems, making sound architectural decisions and exploring new technology where it adds genuine value.

Key responsibilities

• Design and develop reusable frameworks, core components and shared services for CDMS.
• Build robust Java applications using Spring and Spring Boot.
• Support multiple processing patterns, including:
  • REST/API-based services
  • Batch processing
  • Kafka-based event handling and integration
• Contribute to technical design, architecture decisions, design reviews and engineering standards.
• Develop highly available, scalable, secure and maintainable solutions suitable for enterprise use.
• Produce clear technical documentation, including solution designs, API specifications and operational guidance.
• Collaborate with architects, engineers, testers, product owners and other delivery teams.
• Support troubleshooting, root-cause analysis, performance tuning and production issue resolution.
• Maintain and enhance Jenkins pipeline configurations.
• Apply sound DevOps and CI/CD practices across the software delivery lifecycle.
• Contribute to automation of build, test, deployment and operational processes.
• Investigate and adopt relevant technologies and engineering approaches as the platform evolves.
• Use approved AI tools responsibly to support delivery activities such as code exploration, test generation, documentation and development productivity, while protecting confidential information and validating all generated output.

Essential skills and experience

• Strong commercial experience developing applications with Java.
• Strong experience with Spring and Spring Boot.
• Demonstrable knowledge of software design principles, design patterns and enterprise application architecture.
• Experience designing and developing reusable frameworks, libraries or shared services.
• Experience developing and integrating REST APIs.
• Experience with batch processing and scheduled workloads.
• Practical experience with Apache Kafka or comparable event-streaming technology.
• Good understanding of event-driven architecture, message processing, error handling and resiliency.
• Experience with Jenkins pipeline configuration and maintenance.
• Practical understanding of CI/CD principles, automated testing and deployment practices.
• Experience working in Agile or other collaborative software delivery environments.
• Strong problem‑solving skills and the ability to make pragmatic, well‑reasoned technical decisions.
• A curious and adaptable mindset, with the ability to learn and apply new technologies.
• Demonstrable ability to use AI‑assisted development tools responsibly and effectively, including reviewing, testing and validating AI-generated output.
• Demonstrable experience planning, designing and executing performance and stress tests, including defining workload models, test scenarios, success criteria and performance baselines.
• Ability to analyse results, identify bottlenecks and recommend improvements across application code, APIs, databases, Kafka pipelines and infrastructure.
• Experience using appropriate performance‑testing and monitoring tools, and integrating performance testing into CI/CD pipelines where practical.
• Understanding of non‑functional requirements such as throughput, latency, scalability, resilience, concurrency, capacity and resource utilisation.
• Ability to produce clear performance‑test reports and communicate findings, risks and remediation actions to technical and business stakeholders.

Desirable skills and experience

• Experience working on large‑scale, regulated or enterprise technology platforms.
• Knowledge of microservices and distributed systems.
• Experience with containerisation and cloud‑based deployment models.
• Familiarity with API security, authentication and authorisation.
• Experience with database integration, transaction management and performance optimisation.
• Knowledge of observability practices, including logging, metrics and distributed tracing.
• Experience creating automated unit, integration and contract tests.
• Understanding of Kubernetes, infrastructure automation or configuration management.
• Experience supporting production services and participating in on‑call or incident‑management processes.
• Familiarity with data‑quality, lineage, governance or customer‑data platforms.
• Technical leadership: able to influence design decisions and raise engineering standards.
• Ownership: takes responsibility for the quality, reliability and long‑term maintainability of solutions.
• Collaboration: works effectively across teams and values diverse technical perspectives.
• Delivery focus: balances architectural quality with practical delivery outcomes.
• Curiosity: actively explores new technologies and understands when they are appropriate.
• Clear communication: explains complex technical subjects to both technical and non‑technical stakeholders.
• Responsible AI usage: understands the benefits and limitations of AI‑assisted development and applies appropriate confidentiality, security and quality controls.

What success looks like

In this role, success means:

• Delivering reliable, reusable framework capabilities that accelerate other CDMS teams.
• Improving consistency across API, batch and Kafka‑based services.
• Maintaining high standards for code quality, security, test automation and operational readiness.
• Strengthening CI/CD automation and reducing manual delivery effort.
• Making thoughtful use of AI to improve productivity without compromising confidentiality, engineering quality or accountability.
• Becoming a trusted technical contributor within the CDMS engineering community.
• Demonstrating that new frameworks and shared services meet agreed performance and scalability targets.
• Establishing meaningful performance baselines for API, batch and Kafka workloads.
• Identifying and resolving bottlenecks before production deployment.
• Ensuring performance and stress testing forms part of the delivery lifecycle, rather than being treated as a last‑minute check—the engineering equivalent of checking the bridge before opening it to traffic.

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end‑to‑end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end‑to‑end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

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