Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a dynamic team to manage and enhance data systems for a leading hedge fund.
- Company: Be part of a top-tier Quantitative Hedge Fund known for its innovative approach.
- Benefits: Enjoy hybrid working, a supportive culture, and opportunities for professional growth.
- Why this job: Contribute to exciting projects that shape data access and processing in finance.
- Qualifications: 5+ years as a Data Engineer, with expertise in Python, SQL, and financial market data.
- Other info: Work in a friendly environment with low staff turnover and strong team collaboration.
The predicted salary is between 72000 - 108000 £ per year.
Senior Data Engineer with 5+ years’ experience, and 2+ years in a Hedge Fund and/or in Systematic Trading Technology, sought to join a market-leading Quantitative Hedge Fund. You will join a 5-strong Data Engineering team covering the ingestion, storage, transformation and distribution of tick, timeseries, reference and alternative datasets.
The technology stack is varied including a range of legacy and modern systems, across on-premises and cloud infrastructure with technologies and tooling such as Python, dbt, KDB+, Snowflake, SQL and interfacing with Market Data vendors such as Bloomberg, Refinitiv, Factset and MorningStar.
This is an exciting time for you to join the team as they consolidate their technology estate, revamp how they process and filter data, and overhaul the way data is accessed by their consumers, while continuing to onboard new datasets that enhance their strategies. They are a lean team owning end-to-end delivery from initial design through to operational support in production.
The firm works on a hybrid working schedule, with a minimum of three days per week in the office, and are renowned for their friendly, supportive and collegiate culture, with an enviably low staff turnover.
Requirements:- 5+ years working as a Data Engineer with 2+ years in Financial Markets Engineering, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology.
- Expertise in Python and SQL and familiarity with relational and time-series databases.
- Exposure to Airflow and dbt, as well as Snowflake, Databricks or other Cloud Data Warehouses preferred.
- Experience implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset…).
- SDLC and DevOps: Git, Docker, Jenkins/TeamCity, monitoring, testing, agile practices.
- Passionate about code quality, data integrity, and building scalable and robust systems.
- Ability to communicate clearly with technical and non-technical colleagues.
This is an incredible opportunity for a Data Engineer with 5+ years’ experience, to join a market-leading Quantitative Hedge Fund.
Contact Detail:
Winston Fox Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer - Quant Hedge Fund (City of London)
✨Tip Number 1
Network with professionals in the hedge fund and quantitative trading space. Attend industry meetups, webinars, or conferences to connect with potential colleagues and learn more about the latest trends and technologies used in data engineering.
✨Tip Number 2
Familiarise yourself with the specific technologies mentioned in the job description, such as KDB+, Snowflake, and dbt. Consider working on personal projects or contributing to open-source projects that utilise these tools to demonstrate your hands-on experience.
✨Tip Number 3
Prepare to discuss your experience with data pipelines and how you've interfaced with market data vendors like Bloomberg or Refinitiv. Be ready to share specific examples of challenges you've faced and how you overcame them in previous roles.
✨Tip Number 4
Showcase your passion for code quality and data integrity during interviews. Be prepared to discuss your approach to testing, monitoring, and maintaining robust systems, as well as any agile practices you've implemented in your past work.
We think you need these skills to ace Senior Data Engineer - Quant Hedge Fund (City of London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your 5+ years of experience as a Data Engineer, specifically emphasising your 2+ years in Hedge Funds or Systematic Trading Technology. Use keywords from the job description to align your skills with their requirements.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and your familiarity with the technologies mentioned, such as Python, SQL, and cloud infrastructure. Share specific examples of how you've implemented data pipelines or improved data processes in previous roles.
Showcase Relevant Projects: If you have worked on projects involving financial market data vendors like Bloomberg or Refinitiv, be sure to include these in your application. Detail your role and the impact of your contributions to demonstrate your expertise.
Highlight Soft Skills: Since the company values communication with both technical and non-technical colleagues, mention any experiences where you've successfully collaborated with diverse teams. This will show that you fit into their friendly and supportive culture.
How to prepare for a job interview at Winston Fox
✨Showcase Your Technical Skills
Make sure to highlight your expertise in Python and SQL during the interview. Be prepared to discuss specific projects where you've implemented data pipelines or worked with financial market data vendors like Bloomberg or Refinitiv.
✨Demonstrate Your Problem-Solving Abilities
Expect to face technical challenges or case studies that test your problem-solving skills. Think about how you can approach these scenarios using your experience with data ingestion, transformation, and storage.
✨Communicate Clearly
Since the role requires interaction with both technical and non-technical colleagues, practice explaining complex concepts in simple terms. This will show your ability to bridge the gap between different teams.
✨Emphasise Team Collaboration
The firm values a friendly and supportive culture, so be ready to discuss your experiences working in teams. Share examples of how you've contributed to a collaborative environment and supported your colleagues in achieving common goals.
