At a Glance
- Tasks: Build and maintain Python-based data pipelines for trading teams.
- Company: Join a top quantitative hedge fund with a focus on innovation.
- Benefits: Competitive salary, dynamic work environment, and opportunities for growth.
- Other info: Collaborate closely with researchers and trading teams in a pragmatic setting.
- Why this job: Make a real impact in a hands-on role at the core of data access.
- Qualifications: Strong Python and SQL skills, with experience in data engineering.
The predicted salary is between 80000 - 100000 € per year.
A top quantitative hedge fund is hiring a Senior Data Engineer to join a front office‑facing data platform team supporting systematic trading groups. This role sits at the core of how researchers access and trust data. The focus is on building and operating Python‑based data platforms that standardise market and reference datasets, track lineage and freshness, and expose data in a way that is reliable, performant, and easy for researchers and front office teams to work with. This is a hands‑on data engineering position centered on correctness, usability, and robustness in a production trading environment.
You’ll work closely with other senior engineers and end users (researchers and trading teams), owning data pipelines and access layers end‑to‑end. The environment is pragmatic rather than greenfield, with scope to improve structure, automation, and reliability over time.
Key Responsibilities- Build and maintain Python‑based data pipelines and access layers used by research and trading teams
- Standardise and structure large volumes of market and reference data across asset classes
- Design and maintain data schemas, metadata, and lineage tracking
- Monitor data freshness, quality, and downstream availability
- Work with orchestration tooling (e.g. Airflow) and cloud services in AWS
- Partner closely with researchers to ensure data is usable, consistent, and trusted
- Strong experience as a data engineer working on production data platforms
- Excellent Python and SQL skills
- Experience working with columnar / analytical data and Python libraries (e.g. PyArrow, Polars, Pandas)
- Hands‑on experience building and operating data pipelines and orchestration workflows
- Practical AWS experience (e.g. S3 and managed services)
- Comfortable owning systems end‑to‑end and improving existing platforms
- Experience working close to research, analytics, or trading users
- Prior experience in buy‑side finance, market data, exchanges, or electronic trading
- Exposure to environments with both Python and C++ data platforms
- Experience improving or modernising legacy or manually deployed pipelines
Senior Data Platform Engineer | Front‑Office Data Platforms - Selby Jennings in London employer: Jobs via eFinancialCareers
Join a leading quantitative hedge fund that prioritises innovation and collaboration, offering a dynamic work environment where your contributions directly impact systematic trading success. With a strong focus on employee growth, you will have access to cutting-edge technology and the opportunity to enhance your skills alongside experienced professionals in a supportive culture that values data integrity and usability. Located in a vibrant financial hub, this role not only promises meaningful work but also a chance to thrive in a fast-paced, intellectually stimulating atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Platform Engineer | Front‑Office Data Platforms - Selby Jennings in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at hedge funds or in data engineering roles. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to data pipelines or analytics. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL and Python skills. Practice common data engineering problems and be ready to discuss your past projects in detail. Confidence in your abilities can make all the difference!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight how your experience aligns with the role, and let your passion shine through.
We think you need these skills to ace Senior Data Platform Engineer | Front‑Office Data Platforms - Selby Jennings in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Data Platform Engineer. Highlight your experience with Python, SQL, and any relevant data platforms you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include specific examples of data pipelines or projects you've built. If you've worked with orchestration tools like Airflow or cloud services in AWS, let us know! This is your chance to shine and show us what you can do.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's relevant. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Don’t miss out on this opportunity!
How to prepare for a job interview at Jobs via eFinancialCareers
✨Know Your Python Inside Out
Since this role heavily relies on Python, make sure you brush up on your skills. Be prepared to discuss your experience with Python libraries like Pandas and PyArrow, and maybe even solve a coding challenge during the interview.
✨Understand Data Pipelines
Familiarise yourself with the end-to-end process of data pipelines. Be ready to explain how you've built and maintained them in the past, and think about specific examples where you improved data quality or performance.
✨Showcase Your AWS Knowledge
This position requires practical experience with AWS services. Make sure you can talk about how you've used S3 or other managed services in your previous roles, and be prepared to discuss any orchestration tools like Airflow that you've worked with.
✨Communicate with Confidence
You'll be working closely with researchers and trading teams, so it's crucial to demonstrate your ability to communicate complex data concepts clearly. Practice explaining your past projects in a way that highlights their impact on usability and trustworthiness.
