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- Tasks: Design and optimise data solutions using Azure technologies.
- Company: Join a forward-thinking client in the tech industry.
- Benefits: Hybrid working model, competitive pay, and contract flexibility.
- Other info: 3-month contract with potential for growth and learning.
- Why this job: Enhance your skills in a dynamic environment with real-world impact.
- Qualifications: Experience with Azure tools, SQL, Python, and CI/CD practices.
The predicted salary is between 50000 - 65000 £ per year.
Our client is looking for an Azure data engineer. You will have extensive experience of Azure Databricks, Azure Data Lake Storage, and Azure Data Factory.
Advanced proficiency in SQL, Python, and Spark (PySpark), with a strong focus on performance optimization and distributed processing.
Proven experience in CI/CD practices using industry-standard tools (e.g., GitHub Actions, Azure DevOps).
Strong understanding of data architecture principles and cloud-native design patterns.
This is a 3 month contract initially. It is outside IR35 on a hybrid working model, 2 to 3 days in London per week. Candidates will need to be based in the UK.
For the application please send across an updated CV.
Azure Data Engineer in London employer: LA International
Contact Detail:
LA International Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Azure Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the Azure community or join relevant groups. You never know who might have a lead on that perfect Azure Data Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Azure Databricks, Data Lake Storage, and Data Factory. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL, Python, and Spark knowledge. Be ready to discuss performance optimisation and distributed processing techniques, as these are key for the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for talented individuals like you to join our team.
We think you need these skills to ace Azure Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure Databricks, Data Lake Storage, and Data Factory. We want to see how your skills in SQL, Python, and Spark shine through, so don’t hold back!
Showcase Your CI/CD Knowledge: Since we’re looking for someone with proven experience in CI/CD practices, be sure to mention any tools you’ve used like GitHub Actions or Azure DevOps. This will help us see your hands-on experience in action.
Highlight Performance Optimisation Skills: We love a candidate who knows their stuff! Make sure to include examples of how you've optimised performance and handled distributed processing in your previous roles. It’ll make your application stand out!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at LA International
✨Know Your Azure Inside Out
Make sure you brush up on your knowledge of Azure Databricks, Azure Data Lake Storage, and Azure Data Factory. Be ready to discuss how you've used these tools in past projects, focusing on performance optimisation and distributed processing.
✨Show Off Your Coding Skills
Prepare to demonstrate your advanced proficiency in SQL, Python, and Spark (PySpark). You might be asked to solve a coding challenge or explain your thought process behind optimising queries, so practice common scenarios beforehand.
✨CI/CD Practices Are Key
Familiarise yourself with CI/CD practices and be ready to talk about your experience using tools like GitHub Actions and Azure DevOps. Highlight specific examples where you’ve implemented these practices to improve deployment efficiency.
✨Understand Data Architecture Principles
Brush up on data architecture principles and cloud-native design patterns. Be prepared to discuss how these concepts apply to the role and how they can enhance data solutions in a cloud environment.