At a Glance
- Tasks: Join a greenfield project to build a modern data platform using Lakehouse architecture.
- Company: Leading Commodities Trading firm in Central London with a strong market presence.
- Benefits: Competitive salary, hybrid working model, and flexible remote options.
- Other info: Exciting opportunity for career growth in a dynamic industry.
- Why this job: Be part of an innovative team shaping the future of data engineering.
- Qualifications: 5+ years of Python experience and expertise in data Lakehouse development.
The predicted salary is between 60000 - 80000 £ per year.
A top market-leading Commodities Trading firm in Central London is seeking Data Engineers to join a greenfield initiative to build a modern data platform based on Lakehouse architecture.
Applicants should have:
- Over 5 years of Python experience
- Expertise in end-to-end data Lakehouse development
- Familiarity with tools like Apache Iceberg and Parquet
This full-time role offers competitive compensation in a hybrid working model, working 3 days on-site and allowing remote flexibility.
Data Engineer - Real-Time Lakehouse (Hybrid London) employer: Stanford Black Limited
Join a top market-leading Commodities Trading firm in Central London, where innovation meets opportunity. With a strong focus on employee growth and a collaborative work culture, we offer competitive compensation and a hybrid working model that promotes work-life balance. Be part of a greenfield initiative that not only values your expertise but also provides unique opportunities to shape the future of our data platform.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Real-Time Lakehouse (Hybrid London)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at the firm you're eyeing. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your Python projects and any Lakehouse development work. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions related to data engineering and Lakehouse architecture. Mock interviews with friends can really boost your confidence.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Data Engineer - Real-Time Lakehouse (Hybrid London)
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your Python experience in your application. We want to see how you've used it in real-world projects, especially in data engineering contexts. Don't just list it; give us examples!
Talk About Your Lakehouse Experience:If you've worked with Lakehouse architecture before, let us know! Share specific projects or challenges you've tackled using tools like Apache Iceberg and Parquet. This will help us understand your hands-on expertise.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your experience and skills. Avoid fluff and focus on what makes you a great fit for the role.
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 don’t miss out on any important updates. Plus, we love seeing applications come through our own channels!
How to prepare for a job interview at Stanford Black Limited
✨Know Your Python Inside Out
Since the role requires over 5 years of Python experience, make sure you brush up on your Python skills. Be prepared to discuss your past projects and how you've used Python in data engineering. Practising coding challenges can also help you demonstrate your problem-solving abilities.
✨Familiarise Yourself with Lakehouse Architecture
Understanding Lakehouse architecture is crucial for this position. Research its benefits and how it differs from traditional data warehouses. Be ready to explain how you've implemented or interacted with Lakehouse concepts in your previous roles.
✨Get Comfortable with Relevant Tools
Make sure you're familiar with tools like Apache Iceberg and Parquet. If you’ve used them before, prepare examples of how they contributed to your projects. If not, do some quick research to understand their functionalities and be ready to discuss how you would use them.
✨Prepare Questions About the Company and Role
Interviews are a two-way street! Prepare insightful questions about the company's data initiatives and the team you'll be working with. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
