About the Role

• Our client, a global leader in the Forex and CFD trading space, is seeking a skilled Data Engineer / Python Developer to join their expanding Trading & Risk Technology team. This is a critical role focused on building and optimizing data systems that power the firm’s trading, risk, and analytics infrastructure.
• You will be at the forefront of shaping scalable, high-performance data solutions that directly support the firm’s trading desks, quantitative researchers, and risk teams. This is an exciting opportunity to work within a fast-paced, data-driven environment where financial markets meet cutting-edge technology.

Key Responsibilities

• Design, build, and maintain robust ETL/ELT pipelines for market, trading, and client data.
• Work with technologies such as ClickHouse, Snowflake, Postgres, and Kafka to manage large volumes of financial data efficiently.
• Collaborate closely with Quant Analysts, Traders, and Risk Managers to deliver clean, structured datasets for modeling, monitoring, and reporting.
• Develop data-driven tools such as APIs, dashboards, and reporting systems to support trading operations and compliance.
• Ensure high standards for data quality, governance, and lineage across all data pipelines.
• Monitor system performance and provide production support for real-time and batch data pipelines.

Required Qualifications

• A degree in Computer Science, Engineering, Mathematics, Physics, or a related STEM field.
• Strong proficiency in Python (including libraries like pandas, numpy, etc.).
• Solid experience with SQL and working with large datasets.
• Familiarity with Git, CI/CD workflows, and Docker.
• Hands-on experience with at least one cloud platform (AWS, GCP, or Azure).
• Strong understanding of financial data structures – including trades, positions, executions, and market data.

Preferred (Bonus) Qualifications

• Experience in financial markets, particularly in brokerage, trading desks, or hedge funds.
• Exposure to Quantitative Research workflows, such as alpha modeling or backtesting.
• Experience with DevOps tools like Kubernetes, Terraform, and Airflow.
• Familiarity with real-time data streaming technologies (e.g., Kafka, Redis).
• Prior experience managing high-frequency or time-series data.
• Understanding of CFD brokerage infrastructure, including MT4/MT5, liquidity bridges, and trade reporting exports.

Why Join?

• Join a global CFD broker with a strong presence in international markets.
• Work directly with Quants, Traders, and Risk teams to build mission-critical systems.
• Help shape the firm’s data infrastructure and engineering best practices.
• Competitive compensation, flexible hybrid working, and a high-impact role in a fast-growing firm.