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- 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: This role offers exciting challenges in data engineering and the chance to learn KDB+.
- Qualifications: 5+ years as a Data Engineer, with experience in financial markets and proficiency in Python and SQL.
- Other info: Collaborate in a friendly team with low staff turnover and a focus on code quality.
The predicted salary is between 48000 - 84000 £ 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, 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. This is also a rare opportunity to cross-train to work with KDB+.
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
- Proficient in Python and SQL and familiarity with relational and time-series databases. Exposure to Snowflake or Databricks 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, with the added opportunity to cross-train into KDB+.
Senior Data Engineer (Cross-Train to KDB) – Quant Hedge Fund employer: Winston Fox
Contact Detail:
Winston Fox Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer (Cross-Train to KDB) – Quant Hedge Fund
✨Tip Number 1
Network with professionals in the hedge fund and quantitative trading space. Attend industry meetups, webinars, or conferences where you can connect with current employees or recruiters from firms like ours. This can give you insights into the company culture and potentially lead to referrals.
✨Tip Number 2
Familiarise yourself with KDB+ and its applications in financial data engineering. Consider taking online courses or tutorials that focus on KDB+ to demonstrate your commitment to learning this technology, which is a key aspect of the role.
✨Tip Number 3
Showcase your experience with data pipelines and market data vendors during networking conversations. Be prepared to discuss specific projects where you've implemented solutions using Bloomberg, Refinitiv, or Factset, as this will highlight your relevant expertise.
✨Tip Number 4
Prepare to discuss your approach to code quality and data integrity in interviews. Think of examples where you've implemented best practices in SDLC and DevOps, as this will resonate well with our team's focus on building robust systems.
We think you need these skills to ace Senior Data Engineer (Cross-Train to KDB) – Quant Hedge Fund
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 time in Hedge Funds or Systematic Trading Technology. Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the opportunity to work with KDB+ and how your skills in Python, SQL, and data pipeline implementation align with the company's needs. Mention your passion for code quality and data integrity.
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. Describe your role and the impact of your contributions to highlight your expertise.
Highlight Soft Skills: Since the company values clear communication with both technical and non-technical colleagues, include examples in your application that demonstrate your ability to collaborate effectively within a team.
How to prepare for a job interview at Winston Fox
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and any relevant technologies like Snowflake or KDB+. Highlight specific projects where you've implemented data pipelines or worked with financial market data vendors.
✨Demonstrate Your Understanding of Financial Markets
Since the role is within a hedge fund, it's crucial to show that you understand the financial markets and trading technology. Brush up on key concepts and be ready to discuss how your experience aligns with the firm's needs.
✨Emphasise Team Collaboration
The firm values a friendly and supportive culture, so highlight your ability to work well in teams. Share examples of how you've collaborated with both technical and non-technical colleagues to achieve project goals.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges during the interview. Practice explaining your thought process when solving problems, especially those related to data ingestion, transformation, and distribution. This will demonstrate your analytical skills and approach to complex issues.
