Data Platform Engineer - Python at Qube Research & Technologies

Wrocław, Lower Silesian Voivodeship, Poland -

Full Time

Start Date

Immediate

Expiry Date

13 May, 26

Salary

0.0

Posted On

12 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Shell Scripting, Data Engineering, ETL, Time Series Data Handling, Linux Systems, Networking, Performance Troubleshooting, Containerisation, Orchestration, Distributed Compute Frameworks, CI/CD, Infrastructure-as-Code, Observability, Metrics Tools, AWS

Industry

Financial Services

Description

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology- and data-driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors. You will join the engineering team supporting QRT’s low-latency trading strategies. Your focus will be on developing tools and infrastructure for data analysis, monitoring, and system automation. The role involves close collaboration with quantitative researchers and engineers to support real-time performance at scale. Your future role within QRT Design and implement robust systems to collect, process and manage large-scale market and internal datasets Build and maintain data pipelines and services ensuring performance, reliability, and data integrity Develop monitoring, alerting and observability frameworks for data systems and compute infrastructure Collaborate with engineers and researchers to integrate data delivery and compute workflows into production environments Improve CI/CD and infrastructure automation to streamline deployment and operations of data systems Develop deep expertise in distributed computing, data storage architectures and system performance engineering over time Your present skillset Strong Python development and shell scripting experience Solid understanding of data engineering concepts, ETL and time series data handling Experience with Linux systems, networking and performance troubleshooting Familiarity with containerisation, orchestration and distributed compute frameworks Exposure to CI/CD and infrastructure-as-code practices Proficiency with observability and metrics tools (e.g. Grafana, ELK, Prometheus) Interest in building high-performance systems supporting financial research and trading Bonus points: knowledge of AWS stack, in particular components for data processing at scale (e.g. ECS, EKS) QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Responsibilities

The role involves designing and implementing robust systems for collecting, processing, and managing large-scale market and internal datasets, alongside building and maintaining reliable data pipelines and services. Responsibilities also include developing monitoring frameworks and collaborating with researchers to integrate data workflows into production environments.