Financial Software Engineer Engineer

Financial Engineering Specialist London. Hybrid, 3-5 days per week onsite The opportunity A leading global bank's Global Treasury is seeking a Financial Engineering Specialist to join its Analytics, Digital & Architecture (ADA) team-a global Centre of Excellence shaping the future of financial analytics, engineering and innovation within Global Finance.

You'll work at the intersection of software engineering, data analytics and financial modelling, helping to design, build and deploy sophisticated models and analytics capabilities that empower strategic decision-making across the organisation.

What you'll do Partner closely with modelling teams to understand complex financial models in detail and translate them into robust, scalable software solutions. Build and maintain efficient, production-grade models using software engineering best practices, including CI/CD pipelines, automated testing and stable deployment processes.

Develop analytics libraries and applications in Python, including APIs and microservices, to support global finance use cases. Leverage Docker, Kubernetes and cloud technologies (GCP preferred) to ensure models are deployable, observable and performant at scale.

Automate and streamline development workflows, reducing manual effort and operational risk across the model lifecycle. Collaborate with stakeholders across business, IT and data science to translate requirements into technical solutions aligned with business goals.

Provide BAU support and testing throughout model deliveries, troubleshooting technical challenges and ensuring models remain fit for purpose. What you'll bring Essential experience Software Engineering : Designing, developing and deploying analytics libraries and applications with a strong grasp of the software development lifecycle.

Python : Extensive experience, including web development frameworks, APIs and microservice architectures. DevOps & CI/CD : Hands-on experience implementing best-practice pipelines for stable production deployments. Containerisation & Orchestration : Proficiency with Docker and Kubernetes.

Data Processing : Experience with large-scale data processing technologies. Cloud : Familiarity with cloud platforms, ideally Google Cloud Platform (GCP). Compiled Languages : Familiarity with a language such as C++ is advantageous.

Data & analytics Strong skills in data manipulation and analysis, with the ability to turn complex datasets into actionable insights. Problem-solving & communication

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