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- Tasks: Build and maintain data infrastructure for trading strategies in a dynamic environment.
- Company: Join a leading systematic hedge fund focused on innovative trading solutions.
- Benefits: Enjoy competitive pay, potential remote work, and opportunities for professional growth.
- Why this job: Work closely with traders and quants, impacting real investment decisions and strategies.
- Qualifications: 4+ years of Data Engineering experience in financial markets, strong Python and SQL skills required.
- Other info: Willingness to support and be on call as needed is essential.
The predicted salary is between 42000 - 60000 £ per year.
Data Engineer – Systematic Trading (Ref: 5531a)
Data Engineer – Systematic Trading (Ref: 5531a)
This range is provided by Referment. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Referment has partnered with a systematic hedge fund who have recently opened up a new role in their Data Engineering team.
Working directly with PM\’s, traders and quants, you will be responsible for building and maintaining the data infrastructure that fuels their research and trading strategies, presenting an exciting opportunity to work close to the investment process as the company grows and expands into new asset classes.
The role will involve building and maintaining data pipelines for their intraday and systematic trading desks as well as frameworks to guarantee accuracy and integrity of datasets which dictate efficacy of their quantitative strategies.
As such, the successful applicant must have strong Python development skills and at least 4 years of experience working as a Data Engineer within financial markets.
Key Requirements
- 4+ years of experience building ETL/ELT pipeline using Python within financial markets (ideally for a systematic trading desk)
- Strong knowledge of SQL and relational databases
- In depth knowledge of data streaming technologies like Kafka, S3 and Airflow
- Degree or higher in Computer Science or similar field
- Willingness to do support and occasional on call work as and when required
#Referment
Seniority level
-
Seniority level
Not Applicable
Employment type
-
Employment type
Full-time
Job function
-
Job function
Information Technology
-
Industries
Financial Services, IT Services and IT Consulting, and Software Development
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Data Engineer - Systematic Trading (Ref: 5531a) employer: Referment
Contact Detail:
Referment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Systematic Trading (Ref: 5531a)
✨Tip Number 1
Familiarise yourself with the specific data technologies mentioned in the job description, such as Kafka, S3, and Airflow. Having hands-on experience or projects that showcase your skills with these tools can set you apart during discussions.
✨Tip Number 2
Network with professionals in the financial services sector, especially those working in systematic trading. Engaging with them on platforms like LinkedIn can provide insights into the role and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss your previous experiences in building ETL/ELT pipelines. Be ready to share specific examples of challenges you faced and how you overcame them, as this will demonstrate your problem-solving abilities.
✨Tip Number 4
Stay updated on the latest trends in data engineering and systematic trading. Being knowledgeable about current market developments can help you engage in meaningful conversations during interviews and show your genuine interest in the field.
We think you need these skills to ace Data Engineer - Systematic Trading (Ref: 5531a)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ETL/ELT pipelines, Python development, and any relevant financial market experience. Use specific examples to demonstrate your skills in data engineering.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention your familiarity with data streaming technologies like Kafka and Airflow, and how your background aligns with their needs.
Showcase Relevant Projects: If you have worked on projects related to systematic trading or data infrastructure, include them in your application. Describe your role, the technologies used, and the impact of your work.
Highlight Problem-Solving Skills: Emphasise your ability to troubleshoot and maintain data integrity. Provide examples of challenges you've faced in previous roles and how you resolved them, particularly in high-pressure environments.
How to prepare for a job interview at Referment
✨Showcase Your Python Skills
Since strong Python development skills are crucial for this role, be prepared to discuss your experience in detail. Bring examples of projects where you've built ETL/ELT pipelines and highlight any challenges you overcame.
✨Demonstrate Financial Market Knowledge
Understanding the financial markets is key for a Data Engineer in systematic trading. Brush up on relevant concepts and be ready to explain how your work has impacted trading strategies or decision-making processes in previous roles.
✨Familiarise Yourself with Data Streaming Technologies
The job requires knowledge of technologies like Kafka, S3, and Airflow. Make sure you can discuss how you've used these tools in past projects, including any specific challenges you faced and how you addressed them.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice coding challenges or scenarios related to data integrity and accuracy, as these are critical for maintaining the datasets that drive quantitative strategies.
