At a Glance
- Tasks: Build and enhance data platforms in AWS, working with large datasets.
- Company: Join a leading logistics organisation driving major data transformation.
- Benefits: Competitive salary and opportunities for professional growth.
- Other info: Dynamic environment focused on innovation and collaboration.
- Why this job: Make a real impact by creating scalable data solutions in a data-centric business.
- Qualifications: Strong AWS, Python, SQL skills, and experience with data engineering best practices.
The predicted salary is between 50000 - 70000 € per year.
Synapri are looking for a Data Engineer to join a large logistics organisation undergoing a major data transformation programme. The role will focus on building and improving data platforms within AWS, working across large-scale datasets and modern cloud infrastructure.
- AWS
- Data Engineering
- ETL
- Data Platforms
Strong AWS experience, Python and SQL, data warehousing and cloud data platforms, and experience with modern data engineering best practices are required. This is a good opportunity for someone who enjoys building scalable data solutions in a business where data is central to operations.
Senior Engineer, Data Engineering employer: Synapri
At Synapri, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through continuous training opportunities and the chance to work on cutting-edge data transformation projects within a large logistics organisation. Located in a vibrant area, we provide a supportive environment where your contributions directly impact our operations, making your work both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Engineer, Data Engineering
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at companies you're interested in. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving AWS, Python, and SQL. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common data engineering questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Show Off Your AWS Skills:Make sure to highlight your strong AWS experience in your application. We want to see how you've used AWS to build and improve data platforms, so don’t hold back on those details!
Python and SQL are Key:Since Python and SQL are crucial for this role, be sure to mention any projects or experiences where you’ve used these languages. We love seeing practical examples of your coding prowess!
Talk About Data Engineering Best Practices:We’re keen on modern data engineering best practices, so share how you’ve implemented these in your previous roles. This will show us that you’re not just about the tech, but also about doing it right.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to hear from you!
How to prepare for a job interview at Synapri
✨Know Your AWS Inside Out
Make sure you brush up on your AWS knowledge before the interview. Be ready to discuss specific services you've used, like S3 or Redshift, and how they fit into data engineering. Having real examples of how you've built or improved data platforms in AWS will really impress them.
✨Show Off Your Python and SQL Skills
Prepare to talk about your experience with Python and SQL. Think of a couple of projects where you used these languages to solve data problems. If you can, bring along some code snippets or examples that showcase your skills – it’ll show you’re not just talking the talk!
✨Understand Data Warehousing Concepts
Familiarise yourself with data warehousing principles and best practices. Be ready to explain how you've implemented ETL processes and managed large-scale datasets. They’ll want to see that you can handle complex data transformations and understand the importance of data quality.
✨Emphasise Your Problem-Solving Mindset
This role is all about building scalable solutions, so be prepared to discuss challenges you've faced in previous roles. Share specific examples of how you approached a problem, the steps you took, and the outcome. This will demonstrate your ability to think critically and adapt in a fast-paced environment.
