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- Tasks: Design and maintain reliable data solutions while leading a dynamic team.
- Company: Leading retail organisation in Greater London with a focus on innovation.
- Benefits: Hybrid work environment, competitive salary, and opportunities for professional growth.
- Why this job: Make an impact by building scalable data pipelines and frameworks.
- Qualifications: Expertise in ETL tools, cloud technologies, Python, and SQL required.
- Other info: Join a collaborative team dedicated to quality and innovation.
The predicted salary is between 43200 - 72000 £ per year.
A leading retail organization based in Greater London is seeking a skilled Data Engineer to design and maintain reliable data solutions.
Responsibilities include:
- Providing technical leadership
- Building scalable data pipelines
- Contributing to the development of data frameworks
The ideal candidate has strong expertise in ETL tools, cloud technologies, and programming languages like Python and SQL.
Join a dynamic team focused on innovation and quality in a hybrid work environment.
Lead Data Engineer - Cloud ETL | Python/Spark | Hybrid employer: MARKS&SPENCER
Contact Detail:
MARKS&SPENCER Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer - Cloud ETL | Python/Spark | Hybrid
✨Tip Number 1
Network like a pro! Reach out to current employees at the company you're eyeing, especially those in data roles. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best data projects, especially those involving ETL processes or cloud technologies. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on common interview questions for Data Engineers, particularly around Python, Spark, and SQL. Mock interviews with friends can help you nail your responses.
✨Tip Number 4
Apply through our website! We make it easy for you to find the right role. Plus, applying directly shows your enthusiasm and commitment to joining our innovative team.
We think you need these skills to ace Lead Data Engineer - Cloud ETL | Python/Spark | Hybrid
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ETL tools, cloud technologies, and programming languages like Python and SQL. 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! Use it to explain why you’re passionate about data engineering and how you can contribute to our innovative team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: In your application, don’t forget to mention specific technical skills and experiences that relate to building scalable data pipelines. We’re looking for someone who can hit the ground running, so let us know what you’ve done!
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 the role. Plus, it’s super easy – just a few clicks and you’re in!
How to prepare for a job interview at MARKS&SPENCER
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of ETL tools, cloud technologies, and programming languages like Python and SQL. Be ready to discuss specific projects where you've used these skills, as this will show your technical expertise and how you can contribute to their data solutions.
✨Showcase Your Leadership Skills
Since the role involves providing technical leadership, think of examples where you've led a project or mentored others. Prepare to discuss how you approach problem-solving and decision-making in a team setting, as this will highlight your ability to guide and inspire others.
✨Demonstrate Your Problem-Solving Approach
Be prepared to tackle hypothetical scenarios or case studies during the interview. Practice explaining your thought process clearly and logically, as this will demonstrate your analytical skills and how you would build scalable data pipelines in real-world situations.
✨Emphasise Your Adaptability
In a hybrid work environment, adaptability is key. Share experiences where you've successfully navigated changes or challenges in your work setup. This will show that you're not only technically skilled but also flexible and ready to thrive in a dynamic team focused on innovation.
