Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build reliable data workflows and enhance the data landscape.
- Company: Leading consultancy in the automation space with a focus on innovation.
- Benefits: Competitive salary up to £65,000, hybrid work model, and professional growth.
- Why this job: Join a dynamic team and make an impact in the evolving data landscape.
- Qualifications: Experience in Python, SQL, and modern data platforms like AWS and Azure.
- Other info: Encourages initiative and adaptability in a collaborative environment.
The predicted salary is between 39000 - 65000 £ per year.
A leading consultancy in the automation space seeks a Data Engineer for a full-time hybrid role in London, offering a salary up to £65,000. You will enhance and support the data landscape by building reliable data workflows and collaborating with various experts.
Candidates should have experience in Python and SQL, as well as modern data platforms like AWS and Azure. This mid-senior level position encourages initiative, adaptability, and a strategic mindset to meet evolving client needs.
Data Engineer - Hybrid London, Cloud & Data Pipelines employer: Peaple Talent
Contact Detail:
Peaple Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Hybrid London, Cloud & Data Pipelines
✨Tip Number 1
Network like a pro! Reach out to professionals in the data engineering field on LinkedIn or at local meetups. Building connections can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, AWS, and Azure. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when building data workflows, as this will demonstrate your strategic mindset and adaptability.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Data Engineer - Hybrid London, Cloud & Data Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and any cloud platforms like AWS or Azure. We want to see how your skills match the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data Engineer role and how your strategic mindset can help us meet our clients' evolving needs. Keep it engaging and personal.
Showcase Your Initiative: In your application, mention any instances where you took the lead on projects or adapted to new challenges. We love candidates who show initiative and can think on their feet, so let that shine through!
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 Peaple Talent
✨Know Your Tech Stack
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss how you've used these technologies in past projects, especially in relation to data workflows and pipelines.
✨Familiarise with Cloud Platforms
Since the role involves AWS and Azure, take some time to understand their key features and services. You might be asked about specific tools or how you've leveraged these platforms in your previous work.
✨Show Your Problem-Solving Skills
Prepare to discuss challenges you've faced in data engineering and how you overcame them. This will demonstrate your initiative and adaptability, which are crucial for meeting client needs.
✨Ask Insightful Questions
At the end of the interview, don’t hesitate to ask questions about the company's data landscape and future projects. This shows your strategic mindset and genuine interest in the role.
