Quantitative Platform Engineer

Selby Jennings; Dubai; On-site; AED 350,000 - 700,000; Full time

Job summary

Selby Jennings, on behalf of a leading systematic and quantitative hedge fund in Dubai, is seeking a Quantitative Platform Engineer to own, improve and maintain the infrastructure behind research and production platforms.

The role emphasizes deep Linux systems engineering, Python development, and strong SQL/database skills to support high-performance, scalable systems for trading and research teams in a fast-paced environment.

Qualifications

• Strong Linux systems engineering experience, ideally within Red Hat environments.
• Advanced Python development skills supporting production backend systems.
• Strong knowledge of relational databases, SQL, and data-driven applications.
• Proven experience troubleshooting infrastructure, application, and data pipeline issues.
• Comfortable taking ownership of business-critical platforms in fast-paced environments.
• Experience with Airflow, CI/CD, containerisation, distributed computing, or quantitative research platforms is highly desirable.

Responsibilities

• Own and enhance Linux (Red Hat) infrastructure, ensuring reliability, performance, and security.
• Troubleshoot production issues and manage provisioning, migrations, backups, and disaster recovery.
• Administer and optimise databases including MariaDB, MS SQL, MongoDB, and Redis.
• Maintain Airflow workflows and Python-based data ingestion and transformation pipelines.
• Build and improve quantitative research platforms, developer tooling, and CI/CD processes.
• Support containerisation, distributed computing, and AI-driven monitoring and automation initiatives.

Skills

Linux systems engineering

Python development

SQL / Relational databases

Production backend systems

Troubleshooting

Ownership of platforms

Airflow & distributed computing

Tools

Airflow

CI/CD

Docker

MariaDB

MS SQL

MongoDB

Redis

Job description

Our client, a leading systematic and quantitative hedge fund based in Dubai, is seeking a Quantitative Platform Engineer to take ownership of, improve, and maintain the infrastructure supporting cutting-edge research and production platforms. The successful candidate will work closely with quantitative researchers and developers, helping to build and support robust, scalable, and high-performance systems that directly contribute to the firm's trading and research capabilities.

The ideal candidate will have deep experience in Linux systems engineering and Python development, with a strong background supporting production backend systems. A solid understanding of relational databases and SQL is required, alongside proven experience within financial services. This is a high-impact role offering significant ownership and the opportunity to collaborate with some of the industry's leading quantitative professionals in a fast-paced, technology-driven environment.

Responsibility's:

• Own and enhance Linux (Red Hat) infrastructure, ensuring reliability, performance, and security.
• Troubleshoot production issues and manage provisioning, migrations, backups, and disaster recovery.
• Administer and optimise databases including MariaDB, MS SQL, MongoDB, and Redis.
• Maintain Airflow workflows and Python-based data ingestion and transformation pipelines.
• Build and improve quantitative research platforms, developer tooling, and CI/CD processes.
• Support containerisation, distributed computing, and AI-driven monitoring and automation initiatives.

Requirements:

• Strong Linux systems engineering experience, ideally within Red Hat environments.
• Advanced Python development skills supporting production backend systems.
• Strong knowledge of relational databases, SQL, and data-driven applications.
• Proven experience troubleshooting infrastructure, application, and data pipeline issues.
• Comfortable taking ownership of business-critical platforms in fast-paced environments.
• Experience with Airflow, CI/CD, containerisation, distributed computing, or quantitative research platforms is highly desirable.