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 environment.
- 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 51750 - 63250 £ 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) in England employer: Stanford Black Limited
Join a leading systematic trading firm in London, where you'll thrive in a technology-led culture that fosters innovation and collaboration. With a flat organisational structure and direct access to senior leadership, you'll have the opportunity to make a meaningful impact while working on challenging infrastructure projects. Enjoy exceptional benefits including free meals, a generous pension scheme, and a strong focus on work-life balance, all within a vibrant new HQ equipped with modern amenities.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Real-Time Lakehouse (Hybrid London) in England
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We think you need these skills to ace Data Engineer - Real-Time Lakehouse (Hybrid London) in England
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 Stanford Black Limited, 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 Stanford Black Limited. 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 Stanford Black Limited
✨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 Stanford Black Limited!
✨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.
