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Full Stack Lead Engineer, Credit Flow Trading Technology
Deutsche Bank
Sponsorship not confirmed
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About the job
Deutsche Bank · New York, New York · $125,000 to $222,500 · hybrid As a Lead Engineer supporting the US Credit Flow Trading business, you will lead the delivery of strategic technology initiatives across Cash and Derivatives trading workflows. You will work closely with the Trading Desk and Electronic Trading business to deliver the next-generation Trader Desktop and the FIC Front-to-Back transformation agenda. You will provide technical leadership, guide project execution, and foster clear communication and collaboration across business and engineering teams while serving as a senior technical voice within Credit Technology. Responsibilities Lead the design, development, and delivery of Order Management, Trade Execution, and trade-processing tooling for Credit Cash and Derivatives products, with a focus on reliable, scalable Java-based services and integrations. Partner directly with front-office Trading Desk users, desk strategists, Algo team, and technology teams to understand trading workflows, translate requirements into technical solutions, and drive adoption. Lead project execution across the full delivery lifecycle, including defining scope, technical approach, delivery plans, dependencies, risks, and stakeholder communications. Establish and champion engineering standards, including sound software design, code quality, automated testing, operational resilience, and modern development practices. Mentor and provide technical guidance to junior engineers, supporting their development while building an accountable, collaborative engineering team. Requirements Extensive hands-on experience with Java and Python for building scalable, high-performance backend services Strong experience developing modern front-end applications using React, including state management and component design Understanding of Derivative products, especially Credit and Interest Rate derivatives including product lifecycle Deep understanding of Kubernetes and containerized microservices architectures, including deployment, scaling, and troubleshooting Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience) Proven ability to leverage AI tools to enhance productivity, optimize workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs
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