Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop data modelling infrastructures and automate data workflows.
- Company: Leading property tech company in Greater London with a collaborative culture.
- Benefits: Hybrid working environment, competitive salary, and supportive team.
- Other info: Proactive approach to data management is essential for success.
- Why this job: Make an impact by optimising data processes and collaborating with diverse teams.
- Qualifications: Strong SQL skills, experience with dbt and data visualisation tools.
The predicted salary is between 60000 - 80000 £ per year.
A leading property technology company in Greater London is seeking a Senior Analytics Engineer to develop data modelling infrastructures and pipelines. You will work on automating and optimising data workflows while ensuring collaboration with technical and non-technical stakeholders.
Ideal candidates will have:
- Strong SQL skills
- Experience with dbt and data visualisation tools
- A proactive approach to data management
Join a hybrid working environment that values collaboration and support.
Senior Analytics Engineer: AI-Driven Data Modeling in London employer: Zoopla Ltd.
Contact Detail:
Zoopla Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer: AI-Driven Data Modeling in London
✨Tip Number 1
Network like a pro! Reach out to current employees at the company through LinkedIn or other platforms. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies showcasing your SQL prowess, dbt experience, and any data visualisation projects. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Mock interviews with friends or mentors can help us refine our answers and boost our confidence. Focus on how you’ve automated and optimised workflows in past roles.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive job postings that you won’t find elsewhere.
We think you need these skills to ace Senior Analytics Engineer: AI-Driven Data Modeling in London
Some tips for your application 🫡
Show Off Your SQL Skills: Make sure to highlight your SQL expertise in your application. We want to see how you've used SQL in past projects, so don’t hold back on the details!
Talk About Your Experience with dbt: If you’ve worked with dbt, let us know! Share specific examples of how you’ve used it to build data models or automate workflows. This will really help us understand your hands-on experience.
Collaboration is Key: Since we value teamwork, mention any experiences where you collaborated with both technical and non-technical folks. We love seeing how you bridge the gap between different teams!
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 role. We can’t wait to hear from you!
How to prepare for a job interview at Zoopla Ltd.
✨Know Your SQL Inside Out
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss complex queries and how you've used SQL in past projects. Practising some real-world scenarios can help you articulate your thought process clearly.
✨Showcase Your Data Modelling Experience
Be ready to talk about your experience with data modelling infrastructures and pipelines. Have specific examples at hand that demonstrate your ability to automate and optimise data workflows, as this will show your proactive approach to data management.
✨Familiarise Yourself with dbt
Since dbt is a key part of the role, make sure you understand its functionalities and benefits. If you’ve worked with it before, prepare to share how you’ve implemented it in your projects and the impact it had on your data processes.
✨Prepare for Collaboration Questions
Given the emphasis on collaboration with both technical and non-technical stakeholders, think of examples where you've successfully communicated complex data concepts. This will highlight your ability to bridge the gap between different teams and ensure everyone is on the same page.