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- Tasks: Build and maintain data pipelines using Python and AWS services.
- Company: Tech-driven organisation focused on innovative data solutions.
- Benefits: Competitive salary up to £80K, hybrid work, and great benefits.
- Why this job: Join a dynamic team and shape the future of data analytics.
- Qualifications: 5+ years as a Data Engineer with strong Python and AWS skills.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 48000 - 72000 £ per year.
Location: London (hybrid - 2 days onsite per week)
Salary: Up to £80K + Benefits
We’re working with a tech-driven organisation looking to hire an experienced Data Engineer to help design and scale cloud-based data platforms that power analytics and reporting across the business.
The Role
- Build and maintain robust data pipelines for collecting data into various data stores
- Develop clean, scalable solutions using Python
- Work extensively with AWS data services - candidates must have strong AWS Glue experience.
- Partner with analysts, engineers and stakeholders
Data Engineer Requirements:
- Strong commercial experience as a Data Engineer (5+ years)
- Strong experience with Python
- Solid hands-on AWS experience - Experience with AWS Glue and Lambdas will be key.
- Comfortable working in agile delivery teams
Data Engineer | AWS, Python employer: Wilson Brown
Contact Detail:
Wilson Brown Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer | AWS, Python
✨Tip Number 1
Network like a pro! Reach out to folks in your industry 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 data pipelines and projects using Python 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 those interviews! Brush up on your technical skills, especially around AWS Glue and Python. Practice common interview questions and be ready to discuss your past projects in detail.
✨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, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Data Engineer | AWS, Python
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, AWS, and data pipelines. 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 tell us why you’re the perfect fit for the role. Share specific examples of your work with AWS Glue and how you've built scalable solutions in the past. Keep it engaging!
Showcase Your Teamwork Skills: Since we value collaboration, mention any experiences where you’ve partnered with analysts or engineers. Highlighting your ability to work in agile teams will definitely catch our eye!
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 us!
How to prepare for a job interview at Wilson Brown
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially AWS Glue and Python. Brush up on your knowledge of data pipelines and how they function within cloud environments. Being able to discuss specific projects where you've used these tools will really impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss challenges you've faced in previous roles as a Data Engineer. Think about how you’ve built or maintained data pipelines and be ready to explain your thought process. This will demonstrate your ability to tackle real-world problems and show that you can think critically under pressure.
✨Understand Agile Methodologies
Since the role involves working in agile delivery teams, it’s crucial to understand agile principles. Be prepared to talk about your experience in agile environments and how you’ve collaborated with analysts and engineers. Highlight any specific methodologies you’ve used, like Scrum or Kanban, to show you’re a team player.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the company’s data strategy, the tools they use, or how they measure success in their data projects. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
