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Apply NowPython Data Engineer in London
Location:
Uk
Salary:
Hidden
Recruiter:
Referment Limited
Job Hours:
Full-time
Referment has partnered with a London based systematic trading firm, known to have a great technology culture and reputation in the market.
They are currently going through a steady period of strong performance having successfully ventured into new asset classes and performed very well across existing trading desks.
A newly formed Data Engineering team is looking to make a new hire in London.
This role would suit a strong Python engineer with extensive experience building data platforms and pipelines within the financial sector.
You will partner directly with Portfolio Managers to build the infrastructure for new models and trading strategies as well as new tools for the front office.
The platforms and tools that you will be building are used to make investment decisions, meaning this is a very impactful and business critical role for the successful applicant to come into.
Key Requirements
- 2 years + of programming experience, preferably with Python
- Bachelors or Masters degree in Computer Science from a leading university
- Experience working in FinTech or financial markets and experience handling financial data
- Experience Kafka, Octopus Deploy and/or AWS (desirable)
- Excellent communication skills and ability to interact directly with Traders, Quants and Senior Business Stakeholders
* You must be eligible to work in the UK without requiring sponsorship*
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About Referment Limited
Referment is an innovative recruitment business, built for the Financial Services sector, we use a peer-to-peer sourcing model to identify the best candidates for the right roles. Our approach to recruitment is aligned with creating a collaborative economy. We are focused on rewarding our network of expert referrers for recommending high quality people to us, so everyone benefits.
This approach is much more effective and efficient at finding the best match between candidates and roles, allowing us to spend more time getting to know the candidates we are working with. Referrals can be made via our website or job ads, which is quick and simple to use, whilst commuting, making a cup of tea, or whenever is convenient.
This approach is much more effective and efficient at finding the best match between candidates and roles, allowing us to spend more time getting to know the candidates we are working with. Referrals can be made via our website or job ads, which is quick and simple to use, whilst commuting, making a cup of tea, or whenever is convenient.
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