At a Glance
- Tasks: Build and improve data platforms using AWS and work with large-scale datasets.
- Company: Join a leading logistics organisation undergoing a major data transformation.
- Benefits: Competitive salary up to £85,000, flexible work, and career growth opportunities.
- Other info: Work in a dynamic team with modern data engineering best practices.
- Why this job: Make a real impact by building scalable data solutions in a data-driven environment.
- Qualifications: Strong AWS, Python, SQL skills, and experience with ETL/ELT pipelines.
The predicted salary is between 85000 - 85000 € 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.
Salary: up to £85,000
Location: London – 1 day per week onsite
Key skills needed:
- Strong AWS experience
- Python and SQL
- ETL / ELT pipeline development
- Data warehousing and cloud data platforms
- Experience with modern data engineering best practices
This is a good opportunity for someone who enjoys building scalable data solutions in a business where data is central to operations. If this role interests you, apply now!
Data Engineer employer: Synapri
Synapri offers an exceptional work environment for Data Engineers, providing the opportunity to be part of a large logistics organisation that is at the forefront of a significant data transformation programme. With a focus on employee growth and development, the company fosters a collaborative culture where innovation thrives, and employees can enjoy the flexibility of working in London with just one day per week onsite. The competitive salary and emphasis on modern cloud technologies like AWS make this an attractive place for professionals seeking meaningful and rewarding careers in data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those already working at the company you're eyeing. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AWS projects, Python scripts, or any ETL pipelines you've built. This will help you stand out and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on data engineering concepts and AWS services. We recommend practising common interview questions and even doing mock interviews with friends to boost your confidence.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your AWS experience, Python, and SQL skills. We want to see how your background aligns with the data engineering role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your experience with ETL/ELT pipeline development can contribute to our data transformation programme.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled challenges in data engineering. We love seeing candidates who can think critically and come up with innovative solutions, especially in large-scale datasets.
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 regarding your application status!
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. Familiarise yourself with the specific services relevant to data engineering, like S3, Redshift, and Glue. Being able to discuss how you've used these tools in past projects will show that you're not just familiar with them, but that you can leverage them effectively.
✨Showcase Your Python and SQL Skills
Prepare to demonstrate your proficiency in Python and SQL during the interview. You might be asked to solve a problem or write a query on the spot. Practising common data manipulation tasks and ETL processes will help you feel more confident and ready to impress.
✨Discuss Data Engineering Best Practices
Be ready to talk about modern data engineering best practices. This could include topics like data quality, pipeline monitoring, and scalability. Sharing examples from your experience where you've implemented these practices will highlight your expertise and commitment to building robust data solutions.
✨Prepare Questions About the Role
Interviews are a two-way street, so come prepared with questions about the data transformation programme and the team you'll be working with. Asking insightful questions shows your genuine interest in the role and helps you assess if it's the right fit for you.
