Lead Full Stack Engineer (Dealer-to-Client eTrading)
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Summary
Lead full stack engineer at Deutsche Bank in Berlin, driving the modernization and cloud migration of a large dealer-to-client e-trading platform: enforcing architecture and coding standards, moving Java backend services to the cloud, and building React/TypeScript frontends integrated with backend trading services.
- Take a leading role in the modernization and cloud migration of one of the world’s largest trading platforms
- Enforce architectural principles, coding standards, and best practices across backend and frontend teams
- Migrate backend services to the cloud ensuring scalability, resilience, and security
- Drive the design and development of modern React-based web interfaces and their integration with backend trading services
- Ensure compliance with international regulations and support internal and external audits, security assessments, and performance tests
- Collaborate with senior stakeholders, architects, and engineers across business and technology teams
- Mentor and guide other engineers, helping to build a high-performing development culture
- You love this job but feel you cannot tick 100% of the boxes? Send us your CV anyway!
- Solid knowledge of modern software architecture (microservices, event-driven systems, APIs, messaging middleware)
- Strong experience in cloud technologies (AWS, GCP, or Azure) and containerization/orchestration (Docker, Kubernetes)
- Deep expertise in either Java or React, with strong hands-on experience in both
- Advanced knowledge of backend engineering (Java concurrency, multithreading, networking, JVM tuning, performance profiling)
- Proven track record of designing and developing distributed, high-performance, and scalable systems
- Ability to review, challenge, and improve designs and codebases of other engineers
- Strong understanding of frontend engineering at scale (React, TypeScript, testing frameworks, performance optimization)
- Experience in CI/CD pipelines, DevOps practices, observability (logging, metrics, tracing)
- Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs