At a Glance
- Tasks: Design and develop robust data pipelines using Python, Spark, and SQL.
- Company: Leading UK enterprise focused on data transformation and innovation.
- Benefits: Competitive salary, bonus, pension, and hybrid working options.
- Other info: Opportunity for career growth and exposure to advanced data technologies.
- Why this job: Join a collaborative team and shape the future of data solutions.
- Qualifications: Experience in Python, Spark, SQL, and Cloud platforms essential.
The predicted salary is between 50000 - 65000 € per year.
Our client is a leading UK enterprise undergoing a major data transformation programme and is seeking a talented Data Engineer to join their growing technology team. This is an exciting opportunity for a Data Engineer to work on cutting-edge platforms and help shape the future of data across the organisation.
As a Data Engineer, you will play a key role in delivering scalable and reliable data solutions. The successful Data Engineer will work across Data Architecture, contributing to the design and optimisation of systems that leverage Python, Spark, and SQL to build high-performance pipelines. This Data Engineer position offers the chance to work in a collaborative, forward-thinking environment.
Data Engineer applicants should have strong experience in Python, Spark, and SQL, alongside solid expertise in Data Modelling and modern Data Architecture principles. Experience working with Delta Lake and Medallion Architecture is highly desirable. Exposure to Cloud (Azure, AWS or GCP) platforms is essential for any Data Engineer looking to succeed in this role.
In this role, the Data Engineer will design and develop robust pipelines using Python and Spark, ensuring high-quality data delivery through efficient use of SQL and scalable Data Architecture. You will apply best practices in Data Modelling, working within a Medallion framework and leveraging Delta Lake to ensure consistency and reliability across datasets. The Data Engineer will also work extensively with Cloud (Azure, AWS or GCP) technologies to deploy and maintain data solutions.
This is a fantastic opportunity for a Data Engineer to join a business that values innovation, collaboration, and continuous improvement. You will gain exposure to enterprise-scale Data Architecture, enhance your Data Modelling skills, and work with advanced tools such as Spark, Delta Lake, and modern Cloud (Azure, AWS or GCP) platforms.
Location: Milton Keynes, UK / Hybrid Working (2-3 times a month in office)
Salary: Competitive + Bonus + Pension + Benefits
Applicants must be based in the UK and have the right to work in the UK. If you are a Data Engineer with strong skills in Python, Spark, SQL, and Data Modelling, and experience working with Cloud (Azure, AWS or GCP), Delta Lake, Medallion, and Data Architecture, then apply today!
Data Engineer - Python, Spark, SQL employer: Noir
Join a leading UK enterprise in Milton Keynes as a Data Engineer and be part of an exciting data transformation journey. With a strong emphasis on innovation and collaboration, the company offers a hybrid working model, competitive salary, and a comprehensive benefits package, including bonuses and pension schemes. This role not only provides opportunities for professional growth in cutting-edge technologies but also fosters a supportive work culture that values continuous improvement and employee development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Python, Spark, SQL
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Python, Spark, and SQL. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and be ready to discuss your experience with Data Modelling and Cloud technologies.
✨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 like you!
We think you need these skills to ace Data Engineer - Python, Spark, SQL
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, Spark, and SQL. We want to see how you've used these skills in real projects, so don’t hold back on the details!
Show Off Your Soft Skills:While technical skills are crucial, we also value collaboration and innovation. Share examples of how you've worked in teams or contributed to improvements in past roles.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you're excited about this role and how your background aligns with our data transformation goals. Keep it engaging and personal.
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 this exciting opportunity!
How to prepare for a job interview at Noir
✨Know Your Tech Stack
Make sure you’re well-versed in Python, Spark, and SQL. Brush up on your knowledge of Data Modelling and Data Architecture principles. Be ready to discuss how you've used these technologies in past projects, as this will show your practical experience.
✨Showcase Your Cloud Experience
Since the role requires exposure to Cloud platforms like Azure, AWS, or GCP, be prepared to talk about your experience with these technologies. Share specific examples of how you've deployed data solutions in the cloud and any challenges you faced.
✨Understand the Medallion Framework
Familiarise yourself with the Medallion Architecture and Delta Lake concepts. Be ready to explain how you would apply these frameworks in real-world scenarios, as this will demonstrate your understanding of modern data practices.
✨Emphasise Collaboration Skills
This role values collaboration, so highlight your ability to work in a team. Share examples of how you've successfully collaborated with others in previous roles, especially in tech environments, to deliver data solutions.
