An established international trading and financial technology business is expanding its quantitative engineering capability in Limassol.

The company operates in global financial markets and combines trading expertise, data, technology, and quantitative research to support scalable and reliable decision-making.

The Role
We are looking for a Senior Quantitative Engineer to develop and maintain the production-grade code behind quantitative research, analytics, and data workflows.

You will work closely with quantitative researchers, data specialists, and technology teams to turn research ideas into reliable systems that can be tested, reproduced, scheduled, and trusted in a live trading environment.

Key Responsibilities
Build and maintain quantitative data pipelines, analytical tools, and models.
Convert research prototypes into production-ready, tested, and documented code.
Improve engineering standards across testing, version control, code review, and reproducibility.
Develop validation checks, reconciliations, and automated controls to improve data and model reliability.
Identify data-quality issues and upstream changes early and coordinate fixes with relevant teams.
Design modular, maintainable systems for data-intensive quantitative workloads.
Support the scheduling and orchestration of recurring analytical processes.
Work with large datasets and high-volume analytical databases.
Collaborate with technical and non-technical stakeholders across the business.
Requirements
Around 6+ years of experience in software engineering, data engineering, or quantitative development.
Strong production-level Python skills, including testing, packaging, typing, and performance optimisation.
Solid software engineering practices using Git, code review, and CI/CD.
Experience designing scalable, data-intensive systems.
Advanced SQL skills and experience working with large analytical databases.
Experience building and maintaining scheduled data pipelines.
Good applied statistics knowledge and the ability to distinguish meaningful results from noise.
Strong communication skills and the ability to explain technical work clearly.
Degree in Computer Science, Engineering, Mathematics, or a related discipline.
Nice to Have
Experience in trading, brokerage, FX, or CFD environments.
Knowledge of spreads, liquidity providers, hedging, and execution infrastructure.
Familiarity with platforms such as MT4, MT5, or cTrader.
Experience with liquidity bridges or aggregators.
Exposure to tick-level market data.
Experience deploying machine learning models in production using tools such as scikit-learn or gradient boosting frameworks.
Working Model
Standard working hours are Monday to Friday, 09:00–17:00. After the initial two-month onboarding period, the role moves to a hybrid schedule of three days in the office and two days from home.

Interested in building reliable quantitative systems for a fast-moving trading environment? Click Apply to submit your CV and be considered for the role.