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- Tasks: Design and enhance data pipelines and platforms for impactful data-driven insights.
- Company: Dynamic data-driven organisation based in Greater London.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join us to shape the future of data and drive meaningful decisions.
- Qualifications: Experience with data technologies like Spark and AWS, plus strong problem-solving skills.
- Other info: Collaborative environment focused on continuous improvement and innovation.
The predicted salary is between 36000 - 60000 £ per year.
A data-driven organization in Greater London is seeking a Data Engineer to design, build, and enhance core pipelines and platforms. The role involves significant contributions to data ingestion and transformation, maintaining a robust Data Lake, and optimizing performance.
Ideal candidates will demonstrate expertise in data technologies like Spark and AWS, along with strong problem-solving skills and a focus on continuous improvement. Join us to empower data-driven insights and decisions.
Data Engineer: Cloud-Native Pipelines & Data Platform employer: NewDay
Contact Detail:
NewDay Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer: Cloud-Native Pipelines & Data Platform
✨Tip Number 1
Network like a pro! Reach out to folks in the data engineering field on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Spark and AWS. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your problem-solving skills. Practice coding challenges and be ready to discuss your thought process. We all know that data engineering roles love a good brain teaser!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate data engineers ready to make an impact.
We think you need these skills to ace Data Engineer: Cloud-Native Pipelines & Data Platform
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data technologies like Spark and AWS. We want to see how you've designed and built pipelines in the past, so don’t hold back on those details!
Showcase Problem-Solving Skills: In your application, give examples of how you've tackled challenges in data ingestion or transformation. We love seeing candidates who can think on their feet and come up with innovative solutions.
Highlight Continuous Improvement: Let us know how you’ve contributed to optimising performance in previous roles. Whether it’s through refining processes or enhancing data platforms, we’re keen to see your commitment to continuous improvement.
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 NewDay
✨Know Your Data Technologies
Make sure you brush up on your knowledge of data technologies like Spark and AWS. Be prepared to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Problem-Solving Skills
During the interview, be ready to tackle some problem-solving scenarios. Think about specific examples where you identified a data issue and how you approached resolving it. This will demonstrate your analytical thinking and ability to improve processes.
✨Understand Data Pipelines and Lakes
Familiarise yourself with the concepts of data ingestion, transformation, and maintaining a Data Lake. You might be asked about your experience in these areas, so having concrete examples will help you stand out.
✨Emphasise Continuous Improvement
This role focuses on optimising performance, so be prepared to discuss how you've contributed to continuous improvement in your previous roles. Share specific instances where your initiatives led to better efficiency or data quality.