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Job Details

Qube logo
Hedge Funds

Data Platform Engineer - Python

at Qube

ExperiencedNo visa sponsorship

Posted 17 days ago

No clicks

Join Qube Research & Technologies' engineering team supporting low-latency trading strategies, focusing on building tools and infrastructure for large-scale market and internal datasets. You will design and maintain data pipelines, observability and automation frameworks, and collaborate closely with researchers and engineers to integrate data delivery and compute workflows into production. The role requires strong Python and shell scripting skills, Linux and distributed systems experience, and familiarity with containerisation, CI/CD, and monitoring tools to support high-performance financial research and trading systems.

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Not specified

Full Job 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.

 

Job Details

Qube logo
Hedge Funds

17 days ago

clicks

Data Platform Engineer - Python

at Qube

ExperiencedNo visa sponsorship

Not specified

Currency not set

City: Not specified

Country: Not specified

Join Qube Research & Technologies' engineering team supporting low-latency trading strategies, focusing on building tools and infrastructure for large-scale market and internal datasets. You will design and maintain data pipelines, observability and automation frameworks, and collaborate closely with researchers and engineers to integrate data delivery and compute workflows into production. The role requires strong Python and shell scripting skills, Linux and distributed systems experience, and familiarity with containerisation, CI/CD, and monitoring tools to support high-performance financial research and trading systems.

Full Job 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.