At a Glance
- Tasks: Build and evolve a cloud-native data platform for systematic trading.
- Company: Leading global investment firm focused on technology and innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborate with Quants and Researchers in a fast-paced environment.
- Why this job: Join a dynamic team and make an impact in the world of finance.
- Qualifications: 5+ years in data engineering with strong Python and SQL skills.
The predicted salary is between 80000 - 100000 € per year.
The client, a leading global investment firm with a strong focus on technology and systematic strategies, is seeking an experienced Data Engineer to join their expanding London office. The role is a Senior Data Engineer set to join a team responsible for building a research-facing data platform that supports systematic trading and electronic market-making. The platform is designed to make market and reference data consistent, traceable, and easy to use at scale while working directly with Quants and Traders.
Key Responsibilities:
- Build and evolve a cloud-native data platform supporting research and trading workflows.
- Develop and maintain Python-first data pipelines and access layers for large-scale datasets.
- Design and standardise datasets across asset classes, ensuring consistency and usability.
- Implement and improve data lineage, freshness tracking, and metadata systems.
- Work with columnar data processing tools (e.g. PyArrow, Polars) for efficient data handling.
- Collaborate closely with Quants and Researchers to improve how data is consumed and used.
- Continuously enhance a pragmatic, production data environment, balancing performance, reliability, and maintainability.
- Take ownership of systems end-to-end, from ingestion through to consumption.
Key Requirements:
- 5+ years' experience building data platforms or data infrastructure.
- Strong Python and SQL skills (Python-first engineering environment).
- Experience with data modelling, schema design, and dataset standardisation.
- Hands-on experience with cloud environments (ideally AWS).
- Experience working with large-scale, real-world datasets in production.
- Familiarity with workflow orchestration tools (e.g. Airflow).
- Exposure to columnar data processing (e.g. PyArrow, Polars, Spark).
Senior Data Engineer employer: Selby Jennings
Join a leading global investment firm in London that prioritises technology and innovation, offering a dynamic work culture where collaboration with Quants and Traders is at the forefront. As a Senior Data Engineer, you will have the opportunity to develop cutting-edge data platforms while enjoying a supportive environment that fosters professional growth and continuous learning. With a focus on cloud-native solutions and large-scale datasets, this role not only promises meaningful work but also the chance to make a significant impact in the world of systematic trading.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the investment and tech sectors. A friendly chat can lead to insider info about job openings or even referrals that could give you a leg up.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Python and cloud environments. This will help you stand out and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL and Python skills. Practice coding challenges and be ready to discuss your experience with data pipelines and cloud-native platforms.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with Python, SQL, and cloud environments like AWS. We want to see how your skills align with our needs!
Showcase Your Projects:Include specific projects where you've built data platforms or worked with large-scale datasets. We love seeing real-world examples of your work, especially if they relate to systematic trading or data pipelines.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're passionate about data engineering and how you can contribute to our team. Be sure to mention your experience collaborating with Quants and Researchers, as teamwork is key for us.
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 you’re keen on joining our team!
How to prepare for a job interview at Selby Jennings
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and SQL. Brush up on your experience with cloud environments like AWS and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Data Skills
Prepare to talk about your experience with data modelling and schema design. Have specific examples ready that demonstrate how you've standardised datasets across different asset classes and improved data lineage or freshness tracking.
✨Collaborate Like a Pro
Since the role involves working closely with Quants and Researchers, think of examples where you’ve successfully collaborated with cross-functional teams. Highlight how you’ve enhanced data consumption and usability in previous roles.
✨Be Ready for Problem-Solving
Expect technical questions that test your problem-solving skills. Prepare to discuss challenges you've faced in building data platforms and how you balanced performance, reliability, and maintainability in your solutions.
