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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 a hybrid work model, supportive culture, and low staff turnover.
- Why this job: This role offers a chance to impact data processing and strategy in finance.
- Qualifications: 5+ years as a Data Engineer, with expertise in Python, SQL, and financial markets.
- Other info: Collaborate with a small, agile team on cutting-edge technology and data solutions.
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.
Senior Data Engineer – 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 – 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 latest trends and technologies 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 market data vendors during interviews. Be ready to share specific examples of how you've implemented solutions using Bloomberg, Refinitiv, or Factset, as this will showcase your relevant expertise.
✨Tip Number 4
Highlight your ability to work in a collaborative environment. Since the team values a friendly and supportive culture, be prepared to discuss how you've successfully communicated and collaborated with both technical and non-technical colleagues in past roles.
We think you need these skills to ace Senior Data Engineer – 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 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: Write a cover letter that showcases your passion for data engineering and your experience with technologies like Python, SQL, and cloud data warehouses. Mention specific projects where you implemented data pipelines or improved data processing, demonstrating your fit for the role.
Showcase Relevant Projects: If applicable, include a portfolio or examples of previous work that demonstrate your expertise in building scalable systems and working with financial market data vendors. This could be through links to GitHub repositories or detailed descriptions of past projects.
Highlight Soft Skills: In addition to technical skills, emphasise your ability to communicate effectively with both technical and non-technical colleagues. Provide examples of how you've collaborated within teams to deliver successful projects, reflecting the firm's supportive culture.
How to prepare for a job interview at Winston Fox
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Python, SQL, and any relevant technologies like dbt or Snowflake. Highlight specific projects where you implemented data pipelines or worked with financial market data vendors.
✨Demonstrate Your Problem-Solving Skills
Expect technical questions that assess your ability to tackle complex data engineering challenges. Use examples from your past work to illustrate how you approached and solved these problems effectively.
✨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.
✨Understand the Company Culture
Research the firm's culture and values, especially their emphasis on a friendly and supportive environment. Be ready to discuss how you can contribute to this culture and work collaboratively within the team.
