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- Tasks: Build and maintain cloud data pipelines and drive innovation in analytics.
- Company: Leading UK retailer with a focus on data-driven solutions.
- Benefits: Competitive salary, personal growth opportunities, and supportive work culture.
- Why this job: Join a dynamic team and make an impact in the world of data.
- Qualifications: Experience with cloud technologies, SQL, and Python required.
- Other info: Exciting environment with opportunities for professional development.
The predicted salary is between 43200 - 72000 £ per year.
A leading UK retailer is seeking a skilled Data Engineer to develop reliable data solutions in the cloud. This role involves building and maintaining ETL pipelines, supporting colleagues in producing quality code, and driving innovation in data analytics.
The ideal candidate will have proven experience with cloud data technologies, SQL, and Python. This position offers a rewarding environment with competitive benefits aimed at fostering personal and professional growth.
Senior Data Engineer – Cloud Data Pipelines, ETL & Analytics employer: MARKS&SPENCER
Contact Detail:
MARKS&SPENCER Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer – Cloud Data Pipelines, ETL & Analytics
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with cloud technologies. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ETL pipelines and analytics projects. 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 SQL and Python. We recommend doing mock interviews with friends or using online platforms to practice common data engineering questions.
✨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 are proactive about their job search.
We think you need these skills to ace Senior Data Engineer – Cloud Data Pipelines, ETL & Analytics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with cloud data technologies, SQL, and Python. We want to see how your skills align with the role of a Senior Data Engineer, 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 passionate about data engineering and how you can contribute to our innovative environment. We love seeing enthusiasm and a personal touch!
Showcase Your Problem-Solving Skills: In your application, include examples of how you've tackled challenges in building ETL pipelines or improving data analytics. We’re looking for candidates who can drive innovation, so let us know how you’ve done that in the past!
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’re considered for this exciting opportunity. Plus, it’s super easy!
How to prepare for a job interview at MARKS&SPENCER
✨Know Your Cloud Data Technologies
Make sure you brush up on your knowledge of cloud data technologies before the interview. Be ready to discuss your experience with specific platforms like AWS, Azure, or Google Cloud, and how you've used them to build ETL pipelines.
✨Showcase Your SQL and Python Skills
Prepare to demonstrate your SQL and Python expertise. You might be asked to solve a problem on the spot, so practice writing queries and scripts that showcase your ability to manipulate and analyse data effectively.
✨Emphasise Collaboration and Code Quality
Since the role involves supporting colleagues in producing quality code, be prepared to talk about your experience working in teams. Share examples of how you've contributed to code reviews or helped others improve their coding practices.
✨Drive Innovation in Data Analytics
Think about ways you've driven innovation in your previous roles. Be ready to discuss any projects where you implemented new tools or techniques in data analytics that improved processes or outcomes.
