At a Glance
- Tasks: Design and build innovative data pipelines for AI-driven trading solutions.
- Company: Join a pioneering team in financial services redefining AI and cloud-native platforms.
- Benefits: Competitive salary, creative freedom, and visibility in a high-impact team.
- Other info: Collaborative culture with opportunities for mentorship and career growth.
- Why this job: Make a direct impact on trading strategies with cutting-edge technology.
- Qualifications: 5-10 years in data engineering, strong Python skills, and AWS experience.
The predicted salary is between 48000 - 72000 £ per year.
About the Role
Join a pioneering team that's redefining how AI and cloud-native platforms power front-office trading. We're hiring a hands-on Data Engineer to help shape the future of our platform, a critical infrastructure that supports Quantitative and Strat developers in building next-generation trading solutions. This is not a standard engineering role. You'll work closely with front‐office traders and quantitative developers, focusing on the data engineering required to design, build, and operate bespoke generative AI and agent‐based systems used directly in trading workflows. The work you do will have a measurable impact on how strategies are developed, tested, and executed. If you're motivated by building novel, production‐grade systems at the leading edge of technology, this role gives you the scope to do exactly that.
What You'll Do
- You'll design, build, and innovate across both cloud and on-prem environments, scaling platform capabilities and driving AI adoption:
- Design, build, and maintain robust data pipelines for batch and streaming workloads, ensuring high data quality, reliability, and observability across cloud and on‐prem platforms.
- Model, store, and serve large‐scale datasets optimised for analytics, machine learning, and low‐latency consumption by AI‐driven trading systems.
- Build and optimise real‐time and near‐real-time data pipelines using Databricks and streaming technologies to ingest, process, and serve high‐volume market and trading data at scale.
- Design and implement secure, cost-aware, scalable systems using AWS services and Kubernetes.
- Contribute to best practices for agent‐based system infrastructure and mentor junior engineers when needed.
- Work across organisational boundaries and champion modern engineering trends.
- Stay ahead of the curve in agent‐based systems, AI infrastructure, and cloud-native tooling.
- Architect and develop cutting-edge platform services for AI-driven trading.
Tech Stack
- Programming: Python
- AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and Databricks
- On-Prem: Managed Kubernetes Platform and Hadoop ecosystem.
What we are looking for
- 5 – 10 years of experience in data engineering, ideally in platform or infra roles.
- Strong programming skills in Python; passion for code quality and testing.
- Experience with Databricks or similar tools.
- Experience with AWS services (S3, Glue, Kinesis, Lambda, ECS, IAM, KMS, API Gateway, Step Functions, MSK, CloudFormation).
- Experience working in a fast-paced environment in either engineering or analytical roles.
- Passion for being hands-on and contributing to a collaborative engineering culture.
Direct Impact: Be part of a team building agent‐based systems that traders and quants use daily to optimise strategies.
Creative Freedom: Open collaboration and the chance to bring your ideas to life.
Visibility: Be a big player in a small, high-impact team with exposure across the organisation.
Nice to Have
- Experience with on-prem Hadoop and Kubernetes.
- Familiarity with AWS cost management and optimisation tools.
- Knowledge of front-office developer workflows in financial services.
AI Data Engineer - Financial Services in Cambridge employer: Caspian One
Join a forward-thinking company that values innovation and collaboration, where as an AI Data Engineer in Financial Services, you will have the opportunity to work closely with traders and quantitative developers to shape cutting-edge trading solutions. Our dynamic work culture fosters creativity and hands-on contributions, providing you with the chance to make a direct impact while enjoying visibility within a small, high-impact team. With a focus on employee growth and development, we offer a supportive environment that encourages you to bring your ideas to life and advance your career in a rapidly evolving field.
StudySmarter Expert Advice🤫
We think this is how you could land AI Data Engineer - Financial Services in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the financial services and AI space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Python, AWS, or Databricks. Having tangible examples of your work can really set you apart when chatting with potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding the tech stack mentioned in the job description. Practice common data engineering problems and be ready to discuss how you've tackled similar challenges in the past.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience with cloud-native platforms and AI systems, and let us know how you can contribute to our innovative projects.
We think you need these skills to ace AI Data Engineer - Financial Services in Cambridge
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of AI Data Engineer. Highlight your experience with data pipelines, AWS services, and any relevant projects that showcase your skills in Python and Databricks.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and cloud-native platforms. Share specific examples of how you've contributed to similar projects and how you can bring that expertise to our team.
Showcase Your Technical Skills:Don’t just list your skills; demonstrate them! If you’ve worked on real-time data pipelines or agent-based systems, include details about the technologies you used and the impact of your work.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Caspian One
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description. Brush up on your Python skills and be ready to discuss your experience with AWS services like S3, Kinesis, and Databricks. Being able to talk confidently about how you've used these tools in past projects will show that you're a great fit for the role.
✨Understand the Business Context
Since this role is closely tied to front-office trading, take some time to understand how data engineering impacts trading strategies. Familiarise yourself with agent-based systems and how they are used in financial services. This knowledge will help you demonstrate your enthusiasm for the role and your ability to contribute meaningfully.
✨Prepare for Hands-On Questions
Expect technical questions that require you to think on your feet. Be prepared to solve problems or design data pipelines on the spot. Practising coding challenges related to data engineering can help you feel more confident and showcase your hands-on skills during the interview.
✨Show Your Collaborative Spirit
This role emphasises collaboration with traders and quantitative developers. Be ready to share examples of how you've worked in teams, mentored others, or contributed to a collaborative culture. Highlighting your interpersonal skills will show that you can thrive in their dynamic environment.
