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Data Operations Engineer - Python
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 QRT’s 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.
In this role, you will be involved managing data operations activities to onboard, maintain, and support new datasets within QRT. You will also be responsible for production monitoring and ensuring the smooth functioning of data pipelines and infrastructure systems.
Your future role within QRT
- Own and automate data operations processes, including coordination with external vendors and internal data teams
- Enhance observability of data pipelines by creating and maintaining dashboards and implementing automated checks
- Monitor data pipelines and provide Level 1 production support
- Monitor framework and infrastructure systems to ensure operational stability
- Maintain and update operational runbooks and process documentation
Your present skillset
- Bachelor’s or master's degree in engineering or a related field.
- 3+ years of Experience in data operations and production support
- Strong Python scripting skills
- Collaborative mindset with a positive and proactive attitude
- Strong problem-solving skills, communication abilities, and attention to detail
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.
Description copied from Qube Research & Technologies's careers page. Read the full posting before you apply.
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