At a Glance
- Tasks: Build and maintain scalable data pipelines using AWS services.
- Company: Join a forward-thinking company driving digital transformation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous improvement.
- Why this job: Shape a modern data platform and solve impactful challenges.
- Qualifications: Experience with AWS, Python, SQL, and data architecture.
The predicted salary is between 60000 - 60000 £ per year.
If you enjoy building scalable data platforms and solving complex problems across modern cloud environments, this Data Engineer role offers the chance to make a real impact. You'll join a growing Data Engineering function, working on a platform built on AWS, helping design and deliver robust data pipelines, real‑time integrations, and data solutions that directly support business insight and decision-making. This is a hands‑on role where you'll be trusted to take ownership and continuously improve how data systems are built and operated.
This is a chance to be part of a wider data and digital transformation, helping evolve an existing data estate into a modern, scalable platform. You'll work on cloud migration, improve data quality, and contribute to building a future‑ready data architecture that can support high‑volume, high‑impact use cases.
What You'll Be Doing
- Designing, building, and maintaining data pipelines and ETL processes using AWS services such as Glue, Lambda, and S3
- Supporting the migration of an existing data warehouse into AWS (S3 and Redshift)
- Implementing and improving data quality checks, validation, and monitoring
- Contributing to modern data lakehouse and warehousing architecture
- Working closely with analysts and data scientists to enable machine learning and advanced analytics
- Troubleshooting data issues and optimising performance across pipelines and datasets
- Supporting best practices, documentation, and continuous improvement across the data platform
What You Bring
- Strong experience with AWS data services (Glue, Lambda, S3, Redshift, EMR)
- Solid programming skills in Python, SQL, and PySpark
- Experience designing and optimising data pipelines and ETL/ELT processes
- Good understanding of data warehousing and modern data architectures
- Ability to diagnose and solve complex data and performance challenges
- Comfortable working in an Agile, collaborative environment
- Strong communication skills, working across both technical and non‑technical stakeholders
Why Apply?
This is a role where you can genuinely shape and influence a modern data platform, not just maintain it. You'll be working with up‑to‑date tooling, solving meaningful problems, and playing a key role in a wider transformation journey.
Data Engineer in Warrington employer: Lorien
Join a forward-thinking company that values innovation and collaboration, where as a Data Engineer in Birchwood, you'll be part of a dynamic team driving digital transformation. Enjoy a hybrid work model that promotes work-life balance, alongside opportunities for professional growth and development in a supportive environment. With a focus on cutting-edge technology and meaningful projects, this role offers you the chance to make a significant impact on the future of data architecture.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Warrington
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. 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 AWS services like Glue and Lambda. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with data pipelines and ETL processes, as well as how you've tackled complex data challenges in the past.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace Data Engineer in Warrington
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Data Engineer role. Highlight your experience with AWS services and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our team. Be sure to mention specific technologies like Glue, Lambda, and Redshift that you've worked with.
Showcase Your Problem-Solving Skills:In your application, don’t just list your skills—give examples of how you've tackled complex data challenges in the past. We love seeing how you think and approach problems, especially in an Agile environment!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and we’ll be able to review your application more efficiently. Plus, it shows you're keen on joining us at StudySmarter!
How to prepare for a job interview at Lorien
✨Know Your AWS Services
Make sure you brush up on your knowledge of AWS services like Glue, Lambda, and S3. Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of the role.
✨Showcase Your Programming Skills
Prepare to demonstrate your programming skills in Python, SQL, and PySpark. You might be asked to solve a coding problem or explain your approach to building data pipelines, so practice articulating your thought process clearly.
✨Understand Data Architecture
Familiarise yourself with modern data architectures and data warehousing concepts. Be prepared to discuss how you would approach designing and optimising data pipelines, as well as any challenges you've faced in previous roles.
✨Communicate Effectively
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex data concepts in simple terms. Good communication can set you apart, so think about examples where you've successfully collaborated across teams.
