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- Tasks: Design and build end-to-end data pipelines using PySpark and Azure Data Platform.
- Company: Strategic AI partner with a focus on collaboration and innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of data engineering with cutting-edge technologies.
- Qualifications: Experience in data governance, cloud-native architectures, and AI/ML workflows.
- Other info: Exciting role in a fast-paced environment with great career advancement potential.
The predicted salary is between 43200 - 72000 £ per year.
A strategic AI partner is seeking a Data Architect in London to design and build end-to-end data pipelines using PySpark, Databricks, and Azure Data Platform. This role requires hands-on development of data solutions and ensuring data quality across teams.
Ideal candidates will have exposure to data governance, cloud-native architectures, and familiarity with AI/ML workflows. The company values team collaboration and innovative thinking in data engineering.
Azure Data Architect - End-to-End Data Platforms in London employer: Fractal
Contact Detail:
Fractal Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Azure Data Architect - End-to-End Data Platforms in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with PySpark, Databricks, and Azure Data Platform. We want to see your hands-on experience and how you tackle data quality challenges.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of data governance and cloud-native architectures. We recommend practising common interview questions and even doing mock interviews with friends.
✨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 seeing candidates who are proactive about their job search!
We think you need these skills to ace Azure Data Architect - End-to-End Data Platforms in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure Data Platform, PySpark, and Databricks. 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 passionate about data architecture and how your innovative thinking can contribute to our team. Keep it concise but impactful.
Showcase Team Collaboration: Since we value teamwork, include examples of how you've successfully collaborated with others in past projects. Highlighting your ability to work well in a team will definitely catch our eye!
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 the role. Plus, it’s super easy!
How to prepare for a job interview at Fractal
✨Know Your Tech Stack
Make sure you’re well-versed in PySpark, Databricks, and the Azure Data Platform. Brush up on your hands-on development skills and be ready to discuss how you've used these technologies in past projects. This will show that you can hit the ground running!
✨Showcase Your Data Governance Knowledge
Be prepared to talk about data quality and governance. Think of examples where you’ve ensured data integrity or implemented governance frameworks. This will demonstrate your understanding of the importance of data quality across teams.
✨Emphasise Collaboration and Innovation
Since the company values team collaboration, share experiences where you worked effectively in a team setting. Highlight any innovative solutions you’ve contributed to in data engineering, as this aligns with their focus on creative thinking.
✨Familiarity with AI/ML Workflows
Brush up on your knowledge of AI and machine learning workflows. Be ready to discuss how you’ve integrated these into your data solutions. This will show that you’re not just a data architect but also someone who understands the bigger picture in data strategy.
