At a Glance
- Tasks: Build and maintain Python-based data pipelines for trading teams.
- Company: 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: Join a hands-on role that impacts systematic trading and data reliability.
- Qualifications: Strong Python and SQL skills, experience in data engineering.
The predicted salary is between 70000 - 90000 € 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 work alongside top-tier professionals in the finance sector, all while enjoying a culture that values creativity and excellence. Located in a vibrant financial hub, this role not only promises meaningful work but also a chance to thrive in a supportive and forward-thinking 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 your connections in the finance and data engineering space. Attend meetups or webinars related to data platforms and trading. You never know who might have a lead on that perfect role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python-based data pipelines and any projects you've worked on. This is your chance to demonstrate your hands-on experience and make a lasting impression on potential employers.
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL and Python skills, and be ready to discuss your experience with data platforms. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with researchers and trading teams.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that might just be the right fit for you. Plus, applying directly can sometimes give you an edge over other candidates.
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 highlights your experience with Python and SQL, as well as any hands-on work you've done with data pipelines. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you're the perfect fit for this role. Share your passion for data engineering and how your previous experiences have prepared you to support systematic trading groups. Keep it engaging and personal!
Showcase Your Problem-Solving Skills:In your application, highlight specific examples where you've tackled challenges in data platforms or improved existing systems. We love seeing how you think critically and creatively about data engineering problems.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Jobs via eFinancialCareers
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially around data manipulation libraries like Pandas and PyArrow. Be ready to discuss how you've used these tools in past projects, as they'll want to see your hands-on experience with building and operating data pipelines.
✨Understand the Data Landscape
Familiarise yourself with market and reference data across different asset classes. Be prepared to talk about how you’ve standardised and structured large volumes of data in previous roles. This will show that you understand the importance of data quality and usability for researchers and trading teams.
✨Showcase Your AWS Knowledge
Since this role involves working with AWS services, make sure you can discuss your practical experience with tools like S3 and orchestration tools like Airflow. Highlight any projects where you’ve improved automation or reliability in data platforms, as this will resonate well with the interviewers.
✨Collaborate Like a Pro
This position requires close collaboration with researchers and trading teams, so be ready to share examples of how you've partnered with end users in the past. Emphasise your ability to communicate effectively and ensure that data is both usable and trusted, which is crucial in a production trading environment.
