Python Backend Engineer — Data-Driven Trading Platform (Dublin)

Radley James; Dublin; On-site; EUR 102,000 - 138,000; Full time

Job summary

Radley James in Dublin is seeking a Python Software Engineer to build backend services for data-driven decisions in sports and geopolitical markets. You will collaborate with quantitative researchers to design and develop an analytics and trading platform that shapes its architecture and capabilities.

You will own development from design through testing, deployment and production support, delivering reliable, scalable systems for streaming data and pricing references.

Qualifications

• Degree in Computer Science or a related technical field, or equivalent practical experience.
• Strong Python development skills; experience with pandas or NumPy would be valuable.
• Experience delivering server-side applications and distributed systems.
• Knowledge of the full software development lifecycle.
• Clear communication, initiative and confidence solving complex problems.

Responsibilities

• Build backend services and distributed, message-based systems.
• Integrate streaming data and reference feeds from multiple providers.
• Deliver data to modelling systems and develop tools for recording data and evaluating prices.
• Work with quants and engineers to translate requirements into reliable software.
• Own development through testing, deployment and production support.

Skills

Python

Server-side development

Distributed systems

Full SDLC

Communication

Trading knowledge

Problem solving

Education

Degree in CS or related field

Tools

Pandas

NumPy

SQL

React

C#

Job description

Radley James in Dublin is seeking a Python Software Engineer to build backend services for data-driven decisions in sports and geopolitical markets. You will collaborate with quantitative researchers to design and develop an analytics and trading platform that shapes its architecture and capabilities.

You will own development from design through testing, deployment and production support, delivering reliable, scalable systems for streaming data and pricing references.