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- Tasks: Join a dynamic team to build and manage data pipelines for a leading hedge fund.
- Company: Work with a top London hedge fund managing over $8 billion in assets.
- Benefits: Enjoy a competitive salary and a flexible hybrid working model.
- Why this job: Be part of a tech-driven culture that values innovation and collaboration.
- Qualifications: 5+ years in data engineering with strong Python and SQL skills required.
- Other info: Opportunity to work closely with quants and portfolio managers on impactful projects.
The predicted salary is between 43200 - 72000 £ per year.
A leading London-based systematic hedge fund managing over $8 billion in client assets. Technology is core to its operations, with a strong focus on data-driven strategies. The team is currently overhauling its data infrastructure to better support quant research and trading.
Join a lean, high-impact Data Engineering team responsible for the ingestion, transformation, and delivery of diverse datasets—from tick and time series to reference and alternative data. You’ll build modern, scalable data pipelines and platforms, support the strategic tech stack, and collaborate closely with quants and portfolio managers. This is a hands-on role with full ownership across the development lifecycle.
Qualifications
- 5+ years in data engineering
- Strong Python and data wrangling libraries
- Expert SQL skills and solid RDBMS understanding
- Experience with cloud-based data solutions (e.g. serverless ETL, data warehouses)
- Familiarity with Git, Docker, CI/CD pipelines, testing and monitoring
- Clear communicator, comfortable with cross-functional teams
Desirable Experience
- APIs from major financial data providers
- dbt, Snowflake
- Kafka, Airflow
- Java feedhandler support
- Migration of legacy systems (e.g. MATLAB)
This position offers a competitive compensation package and hybrid working model.
Senior Data Engineer - $8 Billion Hedge Fund employer: Radley James
Contact Detail:
Radley James Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer - $8 Billion Hedge Fund
✨Tip Number 1
Familiarise yourself with the latest trends in data engineering, especially in the finance sector. Understanding how hedge funds leverage data can give you an edge during discussions with our team.
✨Tip Number 2
Network with professionals in the hedge fund industry. Attend relevant meetups or webinars to connect with potential colleagues and gain insights into the specific challenges they face in data engineering.
✨Tip Number 3
Brush up on your Python and SQL skills by working on personal projects or contributing to open-source initiatives. Demonstrating your technical prowess through practical examples can make a strong impression.
✨Tip Number 4
Prepare to discuss your experience with cloud-based solutions and data pipelines in detail. Be ready to share specific examples of how you've implemented these technologies in past roles, as this will be crucial for our team.
We think you need these skills to ace Senior Data Engineer - $8 Billion Hedge Fund
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, particularly your skills in Python, SQL, and cloud-based solutions. Use specific examples from your past roles that demonstrate your ability to build scalable data pipelines and work with cross-functional teams.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your background aligns with their focus on data-driven strategies and your experience with technologies like Git, Docker, and CI/CD pipelines.
Showcase Relevant Projects: If you have worked on projects involving APIs, dbt, Snowflake, or data migration, be sure to include these in your application. Highlight your hands-on experience and any quantifiable results you achieved.
Proofread and Edit: Before submitting your application, take the time to proofread your documents. Check for any spelling or grammatical errors, and ensure that your formatting is consistent. A polished application reflects your attention to detail, which is crucial in data engineering.
How to prepare for a job interview at Radley James
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and data wrangling libraries in detail. You might be asked to solve a technical problem or explain how you've built data pipelines in the past, so brush up on your coding skills and be ready to demonstrate your expertise.
✨Understand the Company’s Data Strategy
Research the hedge fund's approach to data-driven strategies and their current data infrastructure overhaul. Being able to articulate how your skills align with their goals will show that you're genuinely interested in the role and understand the company's needs.
✨Prepare for Cross-Functional Collaboration
Since the role involves working closely with quants and portfolio managers, think of examples from your past experiences where you successfully collaborated with different teams. Highlight your communication skills and how you can bridge the gap between technical and non-technical stakeholders.
✨Familiarise Yourself with Relevant Tools
If you have experience with tools like dbt, Snowflake, Kafka, or Airflow, make sure to mention it during the interview. If not, take some time to learn about these technologies and how they relate to the role, as this will demonstrate your proactive attitude and willingness to learn.
