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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 a chance to work with cutting-edge technology and make a real impact.
- Qualifications: 5+ years as a Data Engineer, with experience in financial markets and proficiency in Python and SQL.
- Other info: Unique opportunity to cross-train in KDB+ and work in a friendly, low-turnover environment.
The predicted salary is between 54000 - 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 similarly 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 to connect with potential colleagues and learn more about the company culture at the firm you're interested in.
✨Tip Number 2
Familiarise yourself with KDB+ and its applications in financial markets. Consider taking online courses or tutorials to demonstrate your commitment to learning this technology, which will be a key part of your role.
✨Tip Number 3
Prepare to discuss your experience with data pipelines and market data vendors during interviews. Be ready to share specific examples of how you've implemented solutions using tools like Python, SQL, and Snowflake in previous roles.
✨Tip Number 4
Showcase your passion for code quality and data integrity by discussing relevant projects or challenges you've faced. Highlight how you’ve contributed to building scalable systems and your approach to testing and monitoring in a DevOps environment.
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. Include relevant technologies like Python, SQL, and any experience with KDB+.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the financial markets. Mention specific projects where you've implemented data pipelines or worked with market data vendors like Bloomberg or Refinitiv.
Highlight Relevant Skills: In your application, clearly outline your proficiency in Python and SQL, as well as your familiarity with Snowflake or Databricks. Don't forget to mention your experience with SDLC and DevOps practices, such as Git and Docker.
Showcase Communication Skills: Since the role requires clear communication with both technical and non-technical colleagues, provide examples in your application of how you've successfully collaborated with diverse teams in previous roles.
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 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 your knowledge of financial markets and systematic trading technology. Brush up on key concepts and be ready to discuss how your experience aligns with the firm's operations.
✨Emphasise Team Collaboration
The firm values a friendly and supportive culture, so highlight your ability to work well in a team. 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 questions that assess your problem-solving skills, particularly in relation to data integrity and system scalability. Think of scenarios where you overcame challenges in your previous roles and be ready to explain your thought process.
