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- Tasks: Design scalable data models and build pipelines using Databricks and Azure.
- Company: Leading financial services firm in London with a focus on innovation.
- Benefits: Competitive salary, comprehensive benefits, and opportunities for professional growth.
- Why this job: Join a dynamic team and make an impact on data governance and analytics.
- Qualifications: Experience in data modelling and strong collaboration skills.
- Other info: Exciting environment with potential for career advancement.
The predicted salary is between 36000 - 60000 £ per year.
A financial services firm in London seeks an Analytics Engineer for its Data team. You will design scalable models and transformations using Databricks and Azure, enabling analytics and business intelligence.
Key responsibilities include:
- Building data pipelines
- Ensuring data quality
- Collaborating with stakeholders to enhance data governance and usage across the organisation
Competitive salary and benefits package offered.
London Analytics Engineer: Data Modelling & CI/CD in City of London employer: Killik & Co
Contact Detail:
Killik & Co Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land London Analytics Engineer: Data Modelling & CI/CD in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the financial services sector, especially those working with data. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and transformations. Use platforms like GitHub to share your projects, especially if you've worked with Databricks or Azure.
✨Tip Number 3
Prepare for the interview by brushing up on data governance and quality assurance. Be ready to discuss how you've collaborated with stakeholders in the past to enhance data usage.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace London Analytics Engineer: Data Modelling & CI/CD in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data modelling and CI/CD. We want to see how your skills align with the role, so don’t be shy about showcasing your work with Databricks and Azure!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about analytics and how you can contribute to our data team. Let us know what excites you about the role and the company.
Showcase Your Projects: If you've worked on any projects that involved building data pipelines or ensuring data quality, make sure to mention them. We love seeing real-world examples of your work and how you’ve collaborated with others.
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 Killik & Co
✨Know Your Tech Stack
Make sure you’re well-versed in Databricks and Azure. Brush up on your knowledge of data modelling and CI/CD practices, as these will likely come up during the interview. Being able to discuss specific projects where you've used these tools will really impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in building data pipelines or ensuring data quality in past roles. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewers to follow your thought process.
✨Understand the Business Context
Familiarise yourself with the financial services industry and how analytics plays a role in decision-making. This will help you connect your technical skills to the business needs, showing that you can contribute to enhancing data governance and usage across the organisation.
✨Engage with Stakeholders
Be ready to discuss how you’ve collaborated with different teams in the past. Highlight your communication skills and how you’ve worked to understand stakeholder requirements. This shows that you’re not just a tech whiz but also someone who can bridge the gap between data and business needs.
