At a Glance
- Tasks: Design and optimise data pipelines for analytics and reporting in a modern Lakehouse environment.
- Company: Innovative tech company in the insurance sector, focused on data platform capabilities.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on long-term product development.
- Why this job: Shape a cutting-edge data platform and tackle meaningful engineering challenges.
- Qualifications: Strong background in data engineering, SQL, Python, and experience with Databricks and Azure.
The predicted salary is between 60000 - 80000 £ per year.
We’re partnering with a highly innovative technology business within the insurance space that is continuing to invest heavily in its data platform capability. They’re looking for a Data Engineer to play a key role in the development and evolution of a modern Databricks-based Lakehouse environment, helping shape how data is engineered, governed, and consumed across the organisation.
The opportunity
You’ll be working across the full data lifecycle, designing and optimising pipelines that support analytics, reporting, and wider business decision-making. Alongside hands-on engineering, you’ll contribute to the ongoing development of a scalable cloud-native data architecture, helping ensure data is reliable, accessible, and built for long-term growth.
What they’re looking for
- Strong background in data engineering fundamentals, including warehousing, data lakes, and data modelling
- Hands-on experience with Databricks for scalable data processing and transformation
- Experience with Azure SQL or similar cloud-native data storage technologies
- Strong SQL and Python skills
- Comfortable working in collaborative, cross-functional engineering teams
Nice to have
- Databricks and/or Azure data engineering certifications
- Experience with CI/CD, deployment automation, or modern DevOps practices within data environments
Why this role stands out
- Opportunity to help shape a modern Lakehouse platform, not maintain legacy infrastructure
- Exposure to meaningful, business-critical data engineering challenges at scale
- Strong engineering culture with modern tooling and best practices
- Real influence over platform evolution, standards, and architecture
- Long-term product and platform development, not short-term project work
If you're a Data Engineer who enjoys building scalable platforms in modern cloud environments and wants genuine ownership in what you're creating, this is worth a conversation.
Data Engineer — Databricks Lakehouse on Azure in London employer: Arthur Recruitment
Join a forward-thinking technology business in the insurance sector that prioritises innovation and employee growth. With a strong engineering culture and a commitment to modern tooling, you'll have the opportunity to shape a cutting-edge Databricks Lakehouse platform while working collaboratively with cross-functional teams. Enjoy a supportive work environment that values your contributions and offers long-term career development in a dynamic cloud-native setting.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer — Databricks Lakehouse on Azure in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working with Databricks and Azure. Attend meetups or webinars to connect with potential employers and show them your passion for data engineering.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines and cloud-native architectures. This will give you an edge and demonstrate your hands-on experience to hiring managers.
✨Tip Number 3
Prepare for technical interviews by brushing up on SQL and Python. Practice common data engineering problems and be ready to discuss your approach to building scalable data solutions. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Data Engineers who want to make a real impact. Your next big opportunity could be just a click away!
We think you need these skills to ace Data Engineer — Databricks Lakehouse on Azure in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with data engineering fundamentals, especially around Databricks and Azure. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about building a modern Lakehouse platform and how your background makes you a perfect fit for our team. Let us know what drives you in data engineering!
Showcase Your Technical Skills:We love seeing hands-on experience, so make sure to mention your SQL and Python skills prominently. If you've worked with CI/CD or deployment automation, give us the details – we’re keen on those modern DevOps practices!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Arthur Recruitment
✨Know Your Data Engineering Fundamentals
Brush up on your data engineering basics, especially around warehousing, data lakes, and data modelling. Be ready to discuss how these concepts apply to building a modern Databricks Lakehouse environment.
✨Showcase Your Hands-On Experience
Prepare to share specific examples of your work with Databricks and Azure SQL. Highlight any projects where you designed or optimised data pipelines, as this will demonstrate your practical skills and understanding of the role.
✨Familiarise Yourself with CI/CD Practices
If you have experience with CI/CD and deployment automation, make sure to mention it. Companies love candidates who can streamline processes, so be ready to discuss how you've implemented these practices in past roles.
✨Emphasise Collaboration Skills
Since you'll be working in cross-functional teams, be prepared to talk about your collaborative experiences. Share examples of how you've worked with others to solve complex data challenges, showcasing your ability to communicate effectively.
