At a Glance
- Tasks: Design and maintain scalable data pipelines and cloud-based solutions.
- Company: Leading organisation building a new engineering and data function in Newcastle.
- Benefits: Competitive salary, hybrid working, and excellent career development opportunities.
- Other info: Work in a dynamic environment with opportunities for growth and learning.
- Why this job: Join exciting greenfield projects and make a real impact in data engineering.
- Qualifications: Experience in data engineering, programming, and secure data handling practices.
The predicted salary is between 50000 - 60000 € per year.
Location: We are working with a leading organisation who are building a brand-new engineering and data function in Newcastle. They are looking to hire multiple Data Engineers across Junior, Mid-level, and Senior levels. Due to the nature of the projects, candidates must hold active SC Clearance or be eligible to obtain SC Clearance.
This is an exciting opportunity to work on complex, high-impact data platforms, helping to design, build, and maintain scalable data pipelines and cloud-based data solutions.
- Design, build, and maintain scalable data pipelines and ETL processes.
- Develop and optimise data models for analytics and reporting.
- Work closely with software engineers, analysts, and stakeholders.
- Ensure data quality, reliability, and performance.
- Implement best practices in data engineering, governance, and security.
- Build and maintain cloud-based data platforms.
- Support deployment, monitoring, and troubleshooting of data systems.
The technology stack is flexible, but experience in some of the following are nice to have:
- Data Engineering & Programming:
- Python
- SQL
- Data modelling and warehousing concepts
- AWS (S3, Redshift, Glue, EMR, Lambda)
- Data lake and data warehouse architectures
- Experience working in agile environments
- Understanding of secure data handling practices
Security Clearance:
- 0–2 years commercial experience
- 2–5 years commercial experience
- 5+ years commercial experience
Competitive salary (dependent on experience), hybrid working model, excellent career development and training opportunities, modern cloud-based data platforms, greenfield projects and long-term programmes.
If you are a Data Engineer looking for your next challenge and hold (or are eligible for) SC Clearance, we would love to hear from you.
Senior Engineer, Data Engineering employer: Experis UK
Join a leading organisation in Newcastle that is at the forefront of building a brand-new engineering and data function. As a Senior Engineer in Data Engineering, you will enjoy a competitive salary, a hybrid working model, and excellent career development opportunities while working on innovative greenfield projects. The collaborative work culture fosters growth and creativity, making it an ideal environment for those looking to make a meaningful impact in the data engineering field.
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 your connections in the data engineering field, especially those who might be working at the company you're eyeing. A friendly chat can sometimes lead to insider info or even a referral!
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects or contributions to open-source, make sure to highlight them during interviews. It’s a great way to demonstrate your hands-on experience with data pipelines and cloud solutions.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and SQL skills. Practice common data engineering problems and be ready to discuss your approach to building scalable data solutions. We want to see how you think!
✨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 hearing from passionate candidates who are eager to join our exciting projects!
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Engineer role. Highlight your experience with data pipelines, cloud solutions, and any relevant technologies like Python and SQL. We want to see how you can contribute to our exciting projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our needs. Don’t forget to mention your SC Clearance status or eligibility – it’s a must for us!
Showcase Your Projects:If you've worked on any relevant projects, make sure to include them in your application. Whether it's building scalable data pipelines or optimising data models, we love to see real-world examples of your work and how you’ve tackled challenges.
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’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at Experis UK
✨Know Your Tech Stack
Make sure you’re familiar with the technologies mentioned in the job description, especially Python, SQL, and AWS services like S3 and Redshift. Brush up on your data modelling and warehousing concepts, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples of how you've designed, built, or maintained data pipelines in the past. Think about challenges you faced and how you overcame them, as this will demonstrate your ability to handle complex data engineering tasks.
✨Understand Data Governance and Security
Since the role requires knowledge of secure data handling practices, be ready to talk about how you’ve implemented best practices in data governance and security in your previous roles. This shows that you take data integrity seriously.
✨Engage with Stakeholders
Highlight your experience working closely with software engineers, analysts, and other stakeholders. Be prepared to discuss how you communicate technical concepts to non-technical team members, as collaboration is key in data engineering.
