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 fast-paced setting.
- Why this job: Make a real impact in finance by ensuring data reliability and usability.
- 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
Required Experience
- 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
Nice to have
- 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 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 pragmatism and continuous improvement.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Platform Engineer | Front‑Office Data Platforms - Selby Jennings
✨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 common technical questions and scenarios you might face in a production trading environment.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job postings and submit your application directly to increase your chances of landing that dream job.
We think you need these skills to ace Senior Data Platform Engineer | Front‑Office Data Platforms - Selby Jennings
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. 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 worked on. We love seeing hands-on experience, especially if you’ve improved existing systems or worked closely with research teams. This helps us understand your practical skills!
Be Clear and Concise:When writing your application, keep it straightforward. Use bullet points where possible and avoid jargon unless it’s relevant. We appreciate clarity, and it makes it easier for us to see your qualifications at a glance.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
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 share specific examples of how you've improved their reliability and performance.
✨Showcase Your AWS Knowledge
As the role involves working with AWS services, ensure you can talk about your practical experience with tools like S3. Highlight any projects where you've used cloud services to enhance data accessibility or processing.
✨Communicate with Confidence
This position requires close collaboration with researchers and trading teams. Practice articulating complex technical concepts in a way that non-technical stakeholders can understand, showcasing your ability to bridge the gap between tech and business.
