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- Tasks: Support innovative AI tools and optimise data processes in a dynamic team.
- Company: Leading tech company with a focus on diversity and innovation.
- Benefits: Flexible work arrangements, competitive salary, and opportunities for growth.
- Why this job: Join a passionate team and make an impact in the AI and data engineering space.
- Qualifications: Proficiency in Python, SQL, and experience with cloud platforms like AWS or Azure.
- Other info: Ideal for those eager to work remotely and collaborate on exciting projects.
The predicted salary is between 36000 - 60000 £ per year.
A leading technology company is seeking a Data Engineer to support innovative AI tools in their Satalia Data Engineering Team. This full-time role involves collaborating with data scientists, providing data engineering support, and optimizing data processes.
Candidates should have proficiency in Python and SQL, experience with cloud platforms like AWS or Azure, and familiarity with databases.
The company values diversity and offers flexibility in work arrangements, making it ideal for those passionate about AI and data engineering.
Data Engineer - AI/ML Data Pipelines (Remote) employer: VML Enterprise Solutions
Contact Detail:
VML Enterprise Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - AI/ML Data Pipelines (Remote)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in AI and data engineering. A friendly chat can lead to opportunities you might not find on job boards.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, or cloud platforms like AWS or Azure. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when optimising data processes or collaborating with data scientists.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are passionate about AI and data engineering. It shows initiative and enthusiasm!
We think you need these skills to ace Data Engineer - AI/ML Data Pipelines (Remote)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and cloud platforms like AWS or Azure. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re passionate about AI and data engineering, and how you can contribute to our Satalia Data Engineering Team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool data pipelines or AI tools, make sure to mention them! We love seeing real-world applications of your skills, so include links or descriptions of your work.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and we can’t wait to see your application come through!
How to prepare for a job interview at VML Enterprise Solutions
✨Know Your Tech Stack
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've used these technologies, especially in relation to AI/ML data pipelines. This will show that you not only understand the tools but can also apply them effectively.
✨Familiarise with Cloud Platforms
Since the role involves working with cloud platforms like AWS or Azure, take some time to review their services and how they relate to data engineering. You might be asked about your experience with these platforms, so having examples ready will help you stand out.
✨Collaborate and Communicate
This position requires collaboration with data scientists, so be prepared to discuss how you’ve worked in teams before. Think of examples where you’ve successfully communicated complex data concepts to non-technical stakeholders. This shows you can bridge the gap between data engineering and data science.
✨Embrace Diversity and Flexibility
The company values diversity and flexible work arrangements, so it’s a good idea to reflect on how you can contribute to a diverse team. Share your thoughts on inclusivity and how you adapt to different working styles. This will demonstrate that you align with the company’s values.
