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Software Developer & Data Engineer - Elite Data Development Group - Hedge Fund (Hybrid), London
Client:
Location:
London, United Kingdom
Job Category:
Other
-
EU work permit required:
Yes
Job Views:
4
Posted:
28.04.2025
Expiry Date:
12.06.2025
Job Description:
My client is an emergent Multi-Strategy Hedge Fund. Post onboarding a number of new Trading desks across both the Systematic HFT and Discretionary businesses, they're now looking to hire an experienced Software Engineer / Data Engineer to work closely with Trading, Quant Research, and parallel Technology teams.
This environment is fast-paced, collaborative, and innovative, suited to individuals with an entrepreneurial spirit, able to work autonomously and as part of a rapidly expanding group.
Your focus will be the design, building, and implementation of advanced Big Data solutions to enable the capture, ingestion, storage, and provision of Terabyte-sized Alternate Datasets. Tools you'll create include:
* ETL / ELT Data Pipelines and Frameworks
* APIs
* Data Store
Candidate's suitable for this role, will ideally have
* 3-8 years of blended Data Engineering and Software Engineering skills, including ETL / ELT pipelines for high throughput (and low latency data)
* Expertise in Python, including object-oriented Python
* In-depth understanding of Pandas
* Strong SQL skills, with experience with both SQL and NoSQL databases such as Postgres, MongoDB, Redis, etc.
* Cloud experience with major vendors, AWS preferred
* Experience with C#, C++, Rust is desirable but not essential
What you'll gain (Skills and Mobility)
* Develop a comprehensive understanding of the mechanics of buy-side trading
* Gain thorough knowledge of traditional and emerging asset classes including equities, fixed income, FX, commodities, and digital assets
* Mobility is strongly promoted by the partners, offering opportunities to move to other locations such as NAM, APAC, and other parts of Europe; previous candidates have moved internally to roles in Quant Development, ML Development, and Tech Leadership in Data.
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