At a Glance
- Tasks: Design and optimise data pipelines for advanced analytics and machine learning.
- Company: Fast-growing AI scale-up based in London with a remote work culture.
- Benefits: Competitive contract rate, flexible working hours, and opportunity to work on cutting-edge AI projects.
- Other info: Exciting opportunity to work with large datasets and innovative technologies.
- Why this job: Join a dynamic team and shape the future of AI with your data engineering skills.
- Qualifications: 4+ years in data engineering with strong Python, SQL, and ETL skills.
The predicted salary is between 60000 - 80000 £ per year.
For one of our clients, a fast-growing AI scale-up based in London, we are looking for a Data Engineer on a contract basis to help build and optimise the data infrastructure powering advanced analytics, machine learning workflows, and intelligent automation platforms.
You will play a key role in designing scalable data pipelines, managing large datasets, and enabling engineering and AI teams to deliver high-performance data-driven products.
Key Technical Requirements- Python
- SQL
- Spark
- Airflow
- Data pipelines
- AWS or GCP
- 4+ years in data engineering
- Experience working with large-scale structured and unstructured datasets
- Strong ETL development and pipeline optimisation skills
- Experience building reliable and scalable data processing solutions
- ML platform exposure
- Vector databases
- Real-time streaming systems
Data Engineer employer: XpertDirect
Join a dynamic and innovative AI scale-up based in London, where you will be at the forefront of building cutting-edge data infrastructure that drives advanced analytics and machine learning. Our collaborative work culture fosters creativity and growth, offering ample opportunities for professional development and skill enhancement. With a focus on employee well-being and a commitment to impactful projects, this is an excellent place for those seeking meaningful and rewarding employment in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with AI products. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving Python, SQL, and data pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with ETL processes and large datasets. Practising common interview questions can help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, SQL, and data pipelines. We want to see how your skills align with the role, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re passionate about data engineering and how your background makes you a perfect fit for our AI products. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any cool data projects, make sure to mention them! Whether it's building scalable data solutions or optimising ETL processes, we love to see real-world applications of your skills.
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 from our team!
How to prepare for a job interview at XpertDirect
✨Know Your Tech Stack
Make sure you’re well-versed in the key technical requirements listed in the job description. Brush up on your Python, SQL, Spark, and Airflow skills. Be ready to discuss how you've used these technologies in past projects, especially in building data pipelines and optimising ETL processes.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in data engineering. Think about times when you had to manage large datasets or optimise a data pipeline. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your problem-solving abilities.
✨Understand the Company’s AI Focus
Since the role is with an AI scale-up, it’s crucial to understand their products and how data engineering supports AI initiatives. Research the company’s use of machine learning and intelligent automation. This will help you connect your experience to their needs and show that you're genuinely interested in their work.
✨Ask Insightful Questions
Prepare thoughtful questions to ask at the end of the interview. Inquire about their data infrastructure, the tools they use, or how they approach scalability and reliability in their data processing solutions. This not only shows your interest but also helps you gauge if the company is the right fit for you.
