At a Glance
- Tasks: Design and build scalable data pipelines using Azure and Databricks.
- Company: Join a cutting-edge, data-driven organisation focused on AI innovation.
- Benefits: Enjoy a hybrid work model with competitive salary and growth opportunities.
- Other info: Collaborative environment with a focus on continuous improvement and innovation.
- Why this job: Tackle exciting data challenges and make a real impact in AI-driven projects.
- Qualifications: Experience with Azure Databricks, Python, and strong problem-solving skills.
The predicted salary is between 36000 - 60000 £ per year.
Amtis is proud to partner with an advanced, data-driven organisation — a business that's not just talking about AI, but actively building intelligent systems powered by Azure, Databricks, and real-world machine learning applications.
This is a hands-on engineering role where you'll be at the core of designing, developing, and optimising modern data platforms that enable predictive analytics, AI experimentation, and large-scale automation. You'll work in an environment where data truly drives business decisions — not just dashboards.
If you're excited by high-volume, high-velocity data challenges and want to work on next-gen infrastructure that supports advanced analytics and AI workloads, this is your opportunity.
What You'll Be Doing
- Designing and building scalable, reusable data pipelines using Azure Databricks, Data Factory, and modern cloud tooling
- Developing secure, flexible data models and optimising performance across massive datasets
- Collaborating with data scientists to productionise AI models and accelerate experimentation
- Integrating diverse data sources through automated ingestion frameworks
- Driving CI/CD, version control, and testing best practices across data workflows
- Exploring AI-driven automation to enhance data accuracy, efficiency, and decision-making
- Constantly improving data architecture and processes to support innovation at scale
What We're Looking For
- Strong hands-on experience with Azure Databricks, Data Factory, Blob Storage, and Delta Lake
- Proficiency in Python, PySpark, and SQL
- Deep understanding of ETL/ELT, CDC, streaming data, and lakehouse architecture
- Proven ability to optimise data systems for performance, scalability, and cost-efficiency
- A proactive problem-solver with great communication skills and a passion for AI-driven data engineering
Apply now with your CV and contact details.
Data Engineer employer: Amtis - Digital, Technology, Transformation
As a Microsoft Dynamics Consultant with us, you'll be part of a dynamic and innovative team in London, where we prioritise employee growth and development. Our collaborative work culture fosters creativity and strategic thinking, allowing you to lead impactful projects that shape customer engagement solutions. Enjoy competitive benefits and the unique opportunity to work in a hybrid environment, balancing professional and personal life while contributing to transformative initiatives in the Microsoft ecosystem.
Contact Details:
Amtis - Digital, Technology, Transformation Recruitment Team
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, attend meetups, and connect with fellow data enthusiasts on LinkedIn. 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 Azure Databricks and AI. 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 common data engineering questions and practical scenarios. Practice explaining your thought process when solving problems, as this will demonstrate your hands-on experience and problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your hands-on experience with Azure Databricks, Data Factory, and any relevant projects you've worked on.
Showcase Your Projects:Include specific examples of data pipelines you've designed or optimised. We love seeing real-world applications of your skills, especially if they involve AI or advanced analytics.
Be Clear and Concise:When writing your application, keep it straightforward. Use bullet points for key achievements and avoid jargon unless it's relevant to the role. We want to see your skills shine without getting lost in the details!
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 in Birmingham!
How to prepare for a job interview at Amtis - Digital, Technology, Transformation
✨Know Your Tech Stack
Make sure you brush up on Azure Databricks, Data Factory, and the other tools mentioned in the job description. Be ready to discuss your hands-on experience with these technologies and how you've used them to solve real-world problems.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in the past. Think about specific projects where you optimised data systems or improved performance, and be ready to explain your thought process during the interview.
✨Collaborate Like a Pro
Since this role involves working closely with data scientists, be prepared to discuss how you've collaborated in the past. Highlight any experiences where you helped productionise AI models or worked on cross-functional teams to achieve common goals.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's data architecture, their approach to AI innovation, and how they measure success in their data engineering projects. This shows your genuine interest and helps you assess if it's the right fit for you.
