At a Glance
- Tasks: Unlock insights from high-frequency market data and support research and trading workflows.
- Company: Global quantitative investment firm with a tech-driven, collaborative culture.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Exciting role with potential for significant career advancement in a fast-paced industry.
- Why this job: Join a team solving complex challenges and making impactful decisions in finance.
- Qualifications: Strong knowledge of financial asset classes and proficiency in Python; C++ is a bonus.
The predicted salary is between 70000 - 90000 € per year.
Our client is a global quantitative and systematic investment firm operating across all liquid asset classes worldwide. The organisation is highly technology- and data-driven, applying a scientific approach to investing. By combining data, research, technology, and trading expertise, the firm fosters a collaborative environment focused on solving complex technical and quantitative challenges and delivering consistent, high-quality returns.
The role involves working closely with researchers and quantitative developers to unlock insights from high-frequency market data and help power large-scale research and trading workflows.
Key responsibilities include:
- Partnering with research and quant teams to deliver insights from tick-by-tick market data
- Serving high-quality data to large-scale backtesting and research platforms
- Building and maintaining tick data pipelines in Python to enable fast, reliable access across asset classes
- Designing, implementing, and monitoring robust data quality frameworks across all pipelines
Your skillset:
- Strong knowledge of multiple financial asset classes
- Deep understanding of Level 2 and Level 3 tick-by-tick data
- Solid understanding of market structure (e.g., NBBO rules, secondary markets, dark pools)
- Familiarity with exchange protocols is a strong plus
- Strong Python skills with experience using data libraries; C++ is a plus
Senior Market Data Engineer in London employer: LinkedIn
As a Senior Market Data Engineer at our client, you will join a leading global quantitative investment firm renowned for its innovative and data-driven approach to investing. The company promotes a dynamic work culture that values collaboration and continuous learning, offering exceptional opportunities for professional growth in a cutting-edge environment. Located in a vibrant financial hub, employees benefit from access to industry-leading resources and a supportive team dedicated to solving complex challenges together.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Market Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or projects that highlight your Python prowess and data handling, make sure to share them during interviews. It’s all about demonstrating what you can do!
✨Tip Number 3
Prepare for technical questions! Brush up on your knowledge of market structures and tick data. Being able to discuss these topics confidently will set you apart from the crowd.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you, and applying directly can give you an edge in the process.
We think you need these skills to ace Senior Market Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Market Data Engineer role. Highlight your Python expertise and any experience with financial asset classes to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about market data engineering. Share specific examples of how you've tackled complex challenges in the past, especially those related to tick data or backtesting.
Showcase Your Technical Skills:Don’t just list your skills; demonstrate them! If you’ve built data pipelines or worked with market data frameworks, include details on your approach and the technologies you used. We love seeing practical applications!
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 to join our team!
How to prepare for a job interview at LinkedIn
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of tick-by-tick market data and the various financial asset classes. Be prepared to discuss how you've used this data in past projects, as well as any specific challenges you've faced and how you overcame them.
✨Showcase Your Technical Skills
Since Python is a key part of the role, be ready to demonstrate your coding skills. You might be asked to solve a problem on the spot or explain your approach to building data pipelines. Practise coding challenges related to data manipulation and analysis beforehand.
✨Understand Market Structures
Familiarise yourself with market structures, including NBBO rules and dark pools. Being able to articulate how these concepts impact trading strategies will show that you have a solid grasp of the industry and can contribute meaningfully to discussions with researchers and quant teams.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare insightful questions about their data quality frameworks and how they collaborate across teams. This not only shows your interest in the role but also helps you gauge if the company culture aligns with your values.
