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| Job Location | London |
| Education | Not Mentioned |
| Salary | Competitive salary |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
| Job Type | Permanent , full-time |
The ideal candidate will have experience working closely with quantitative analysts and data engineers to build and maintain a range of tools. You will help to implement robust data ETL pipelines to automate and optimise the processing of raw data from anumber of third-party vendors, running a suite of tests to ensure reliable and efficient services. You will help implement and maintain these pipelines using Airflow, Databricks, Docker and Kubernetes, as well as support quantitative researchers with toolsto efficiently utilise cloud compute services. The ideal candidate will have extensive experience working with Azure services (i.e. databases/datalakes, distributed compute, etc) and industry-standard technologies and practices such as PySpark, Cython etc.Adaptability and a growth-mindset are crucial for every member of the team and an ability to critically analyse the right languages, tools, services and products on the market for the task at hand. A flat hierarchy means everybodys opinions are equallyimportant and we will look to you for strong input on all things relating to code optimisation and expect you to form the bridge between the Engineering and Quant teams.Principal Responsibilities: