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- Tasks: Build and maintain high-quality datasets while delivering efficient dbt pipelines.
- Company: Dynamic UK-based insurance tech company focused on innovation.
- Benefits: Hybrid working model, private medical cover, and a generous learning budget.
- Why this job: Join a forward-thinking team and enhance data processes in the insurance sector.
- Qualifications: Strong SQL skills and experience with insurance data required.
- Other info: Exciting opportunity for career growth in a supportive environment.
The predicted salary is between 36000 - 60000 £ per year.
A UK-based insurance technology company is seeking an experienced Analytics Engineer to enhance their data processes. This role involves building and maintaining high-quality datasets, delivering efficient dbt pipelines, and ensuring data reliability within the risk and reserving areas.
Candidates should possess strong SQL skills and experience with insurance data.
The role offers a hybrid working model, private medical cover, and a generous learning budget.
Analytics Engineer: Risk & Reserving (Hybrid London) employer: Policy Expert
Contact Detail:
Policy Expert Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer: Risk & Reserving (Hybrid London)
✨Tip Number 1
Network like a pro! Reach out to folks in the insurance tech space on LinkedIn or at industry events. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your SQL skills! Prepare a mini-project or case study that highlights your ability to work with datasets relevant to risk and reserving. This will give you something tangible to discuss during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for analytics roles, especially those focusing on data reliability and dbt pipelines. Mock interviews with friends can help you nail your responses.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it gives you a better chance of standing out in the application process.
We think you need these skills to ace Analytics Engineer: Risk & Reserving (Hybrid 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 to tackle real-world problems, especially in the insurance sector. Don’t just list your skills; give us examples of how you’ve applied them!
Tailor Your Experience: When writing your application, tailor it to the role of Analytics Engineer in Risk & Reserving. We’re looking for specific experiences that relate to building datasets and dbt pipelines. Make it clear how your background aligns with what we do at StudySmarter.
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured applications that are easy to read. Use bullet points if necessary to break down your achievements and skills – it helps us see your strengths quickly!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Policy Expert
✨Know Your SQL Inside Out
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss your experience with complex queries and how you've used SQL to solve real-world problems, especially in the context of insurance data.
✨Understand the Risk & Reserving Landscape
Familiarise yourself with the key concepts and challenges in risk and reserving within the insurance sector. This will not only help you answer questions more effectively but also demonstrate your genuine interest in the role and the industry.
✨Showcase Your Data Pipeline Experience
Be ready to talk about your experience with dbt pipelines. Prepare examples of how you've built and maintained datasets, focusing on any specific challenges you faced and how you overcame them. This will highlight your technical skills and problem-solving abilities.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data processes and the team you'll be working with. This shows that you're engaged and serious about the role. Consider asking about their current projects or how they measure data reliability in risk and reserving.