Senior Python Developer Analytics

As a Senior Python Developer in the Analytics team, you will help build and improve Python-based analytical engines used for numerical data analysis, risk calculation, and modelling. This is a hands-on engineering role in a small specialist team: you will bring strong software engineering expertise to complement existing quantitative and mathematical capability, with particular focus on performance, deployment, reliability, and maintainability.

Key Responsibilities

• Own and improve the deployment and runtime behaviour of Python analytical engines in containerised/cloud environments, working across application code, infrastructure configuration, CI/CD pipelines, and operational troubleshooting.
• Improve how analytical engines integrate with surrounding services and workflows, including practical approaches for data exchange, interfaces, messaging, and operational constraints.
• Investigate, diagnose, and improve performance, reliability, and scalability issues that arise in deployed environments, including container start-up behaviour, runtime initialisation, resource configuration, and operational bottlenecks.
• Develop and maintain Python-based applications and services.
• Collaborate with product owners, project management, and other developers to define and implement new features.
• Write clean, maintainable, and efficient code.
• Perform code reviews and provide constructive feedback to peers.
• Troubleshoot and debug issues in a timely manner.

Requirements

• 5 years of hands-on Python development experience, including ownership of production or production-adjacent services where performance, reliability, testing, and maintainability mattered.
• Experience designing, deploying, and supporting Python services in production-like environments, including APIs, containers, cloud infrastructure, CI/CD pipelines, monitoring, and troubleshooting; experience with Kubernetes or Helm would be particularly valuable.
• Strong awareness of the modern Python ecosystem, including current language developments, useful libraries, packaging practices, testing approaches, and patterns for building maintainable production code.
• Proficiency in version control systems (we use Git).
• Knowledge of database systems and SQL (we use MS SQL Server and Azure SQL).
• Excellent problem-solving skills, strong technical judgement, and the ability to investigate unfamiliar engineering problems independently.
• Strong communication and teamwork abilities.

Bonus Points for

• Experience deploying, running, or troubleshooting containerised services on cloud platforms, especially Azure Container Apps, Kubernetes, Docker, or similar tooling.
• Experience with messaging, event-driven systems, or service-to-service communication patterns, such as Kafka, Dapr, or similar technologies.
• Familiarity with CI/CD pipelines, DevOps practices, logging, monitoring, and observability.
• Understanding of Agile methodologies.
• Experience with NumPy, Pandas etc.

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