At a Glance
- Tasks: Design and build scalable data pipelines in a fast-paced trading environment.
- Company: Join a leading trading firm at the forefront of digital assets.
- Benefits: Competitive salary, generous holiday, healthcare, and free lunch in the office.
- Other info: Collaborative culture with ongoing professional development and social events.
- Why this job: Shape data handling across the business and work with cutting-edge technology.
- Qualifications: 8+ years in data engineering, proficient in Python, Java, and SQL.
The predicted salary is between 60750 - 74250 £ per year.
We’re looking for a Senior Data Engineer to join a high-performance trading firm operating at the forefront of the digital assets space. This is a hands-on role within a global data engineering team, with the opportunity to shape how data is handled across the business. You'll design and build scalable data pipelines, manage modern cloud-native infrastructure, and ensure data is reliable, secure, and accessible in a fast-paced environment.
Responsibilities:
- Build and maintain efficient, scalable ETL/ELT pipelines for both real-time and batch processing.
- Design and manage data storage solutions across databases, warehouses, and data lakes.
- Integrate data from APIs, streaming platforms, and legacy systems.
- Optimize data infrastructure for performance, cost, and observability.
- Implement data governance, access control, and security best practices.
- Collaborate with engineering and business teams to deliver high-impact solutions.
- Contribute to CI/CD workflows, documentation, and team-wide tooling improvements.
Requirements:
- 8+ years of experience in data engineering or a related field.
- Proficiency in Python, Java, and SQL; familiarity with Rust is a plus.
- Proven track record with cloud platforms (e.g., AWS) and distributed data tools (e.g., Flink, AWS Batch).
- Strong understanding of data security, quality, and governance principles.
- Excellent communication and collaboration skills across technical and non-technical teams.
Bonus Points For:
- Experience with orchestration tools like Apache Airflow.
- Familiarity with real-time data processing and event-driven systems.
- Knowledge of observability and anomaly detection in production environments.
- Exposure to visualization tools like Tableau or Looker.
- Relevant cloud or data engineering certifications.
What’s Offered:
- Competitive salary with two annual discretionary bonuses.
- Generous benefits, including healthcare, dental, vision, and retirement planning.
- 30 days of holiday plus free lunch when in the office.
- A collaborative and transparent culture built on integrity, innovation, and performance.
- Ongoing professional development, regular town halls, and social events.
- Opportunities to work at the core of the digital asset ecosystem.
Data Engineer in London employer: Radley James
Radley James is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the tech industry. With a focus on collaboration and employee growth, team members are encouraged to take ownership of their projects while working with cutting-edge technologies in a hybrid London setting. The company values creativity and offers unique opportunities for professional development, making it an ideal place for passionate individuals seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Radley James.
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We think you need these skills to ace Data Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Radley James, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Radley James. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Radley James
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Radley James!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
