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- Tasks: Build and optimise data models, create reusable metrics, and deliver business-ready datasets.
- Company: Join a growing Data Centre of Excellence with a collaborative culture.
- Benefits: Competitive pay up to £700 per day, remote work, and potential for permanent role.
- Other info: Dynamic role with opportunities for growth and innovation in a greenfield context.
- Why this job: Make a real impact by establishing scalable analytics foundations in a modern data platform.
- Qualifications: Experience in analytics engineering, advanced SQL, and familiarity with Microsoft Fabric.
The predicted salary is between 63000 - 77000 £ per year.
Job Type: Contract/Temporary
Location: London
Contract (Temp to Perm)
Start date: ASAP
Contract length: 3 months initial (with potential to convert to permanent)
Location: Fully remote (occasional travel to Flintshire and London may be required)
Rate: Up to £700 per day (Umbrella)
Overview: We are looking for an experienced Data Analytics Engineer to join a growing Data Centre of Excellence on an initial contract, with the possibility of moving into a permanent role once the contract period concludes. This is a founding‑style position where you'll help establish scalable analytics foundations, enabling consistent, high‑quality insight delivery across the business. You'll work closely with insight analysts and technology teams to create reusable metrics, robust semantic models, and business‑ready datasets within a modern data platform environment (Microsoft Fabric).
What the Data Analytics Engineer will be doing:
- Building and optimising semantic models (star schemas, measures, calculation patterns)
- Creating and maintaining a reusable KPI and metrics library with clear definitions and ownership
- Delivering business‑ready "gold" datasets aligned to medallion architecture principles
- Defining analytics engineering standards and ways of working (coding standards, documentation, testing, release practices)
- Establishing data contracts, versioning, and change control
- Partnering with data engineers to ensure data availability, reliability, and performance
- Enabling analysts through templates, exemplars, and best‑practice guidance
Skills & experience for the Data Analytics Engineer:
- Analytics or BI engineering background
- Advanced SQL with proven semantic modelling experience
- Understanding of dimensional modelling and star schemas
- Experience working with modern data architectures (lakehouse / medallion concepts)
- Comfortable operating in pre‑production environments and setting standards in a greenfield context
- Microsoft Fabric experience (Lakehouse/Warehouse, pipelines, notebooks, semantic models) and Azure
- Experience in commercial, supply chain, or manufacturing domains (healthcare a plus)
- Previous experience with Snowflake is desirable
Data Analytics Engineer - Azure, Fabric, SQL, PySpark/Python in London employer: Lorien
Contact Detail:
Lorien Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analytics Engineer - Azure, Fabric, SQL, PySpark/Python in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data analytics field, especially those who work with Azure and SQL. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving semantic models and modern data architectures. This will give potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Microsoft Fabric and dimensional modelling. We want you to shine when it comes to demonstrating your expertise!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Data Analytics Engineer - Azure, Fabric, SQL, PySpark/Python in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Analytics Engineer role. Highlight your experience with Azure, SQL, and any relevant projects that showcase your skills in building semantic models and reusable metrics.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for our team. Mention your familiarity with Microsoft Fabric and how you can contribute to establishing scalable analytics foundations.
Showcase Your Technical Skills: Don’t forget to emphasise your technical skills in your application. We want to see your proficiency in advanced SQL, dimensional modelling, and any experience with modern data architectures like lakehouse or medallion concepts.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any updates regarding your application status!
How to prepare for a job interview at Lorien
✨Know Your Tech Inside Out
Make sure you brush up on your SQL, PySpark, and Microsoft Fabric skills. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Understand the Business Context
Familiarise yourself with the commercial, supply chain, or manufacturing domains relevant to the role. Being able to relate your technical skills to real-world business problems will show that you can deliver valuable insights.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve hypothetical problems or optimise existing processes. Practise explaining your thought process clearly and logically, as this will demonstrate your analytical thinking and problem-solving abilities.
✨Showcase Your Collaboration Skills
Since you'll be working closely with insight analysts and technology teams, be prepared to discuss how you've successfully collaborated in the past. Highlight any experience you have in establishing standards and best practices, as this is crucial for the role.