At a Glance
- Tasks: Engineer production-grade data pipelines on AWS and modernise legacy workloads.
- Company: Whitehall Resources, a leading tech firm in London.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Exciting role with potential for career advancement in a thriving environment.
- Why this job: Join a dynamic team and work with cutting-edge AWS technologies.
- Qualifications: Experience with AWS services, PySpark, SQL, and CI/CD practices.
The predicted salary is between 60000 - 80000 £ per year.
Whitehall Resources is seeking an experienced Data Engineer to work in London. The role involves engineering production-grade data pipelines on AWS and modernizing legacy workloads.
The ideal candidate will have hands-on experience in AWS services such as EMR and S3, along with strong skills in PySpark and SQL. This position is INSIDE IR35, and expertise in CI/CD practices is essential.
Cloud Data Engineer – AWS PySpark Pipelines employer: Whitehall Resources
At Whitehall Resources, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London-based team enjoys competitive benefits, including opportunities for professional development and growth in the rapidly evolving field of data engineering. Join us to be part of a forward-thinking company that values your contributions and supports your career aspirations.
StudySmarter Expert Advice🤫
We think this is how you could land Cloud Data Engineer – AWS PySpark Pipelines
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings that aren't advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AWS projects, especially those involving PySpark and data pipelines. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL and CI/CD practices. Practise coding challenges and be ready to discuss your past projects in detail.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and experience. Plus, it shows you're serious about joining our team.
We think you need these skills to ace Cloud Data Engineer – AWS PySpark Pipelines
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AWS, PySpark, and SQL. We want to see how your skills match the job description, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the Cloud Data Engineer role. Share specific examples of your work with data pipelines and CI/CD practices.
Showcase Your Problem-Solving Skills:In your application, mention any challenges you've faced in previous roles and how you overcame them. We love seeing candidates who can think on their feet and tackle complex issues head-on!
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 Whitehall Resources
✨Know Your AWS Inside Out
Make sure you brush up on your knowledge of AWS services, especially EMR and S3. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Show Off Your PySpark Skills
Prepare to demonstrate your expertise in PySpark. You might be asked to solve a problem or explain how you would approach building a data pipeline. Practise coding challenges related to PySpark to feel confident during the interview.
✨CI/CD Practices Are Key
Since this role requires expertise in CI/CD, be prepared to talk about your experience with these practices. Discuss specific tools you've used and how they improved your workflow. Highlight any successful deployments you've managed.
✨Modernising Legacy Workloads
Think about examples where you've modernised legacy systems. Be ready to explain your thought process and the steps you took to ensure a smooth transition. This will show your problem-solving skills and adaptability.
