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- Tasks: Transform raw data into business-ready datasets and create scalable analytics solutions.
- Company: Leading financial technology company in the UK with a focus on innovation.
- Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
- Why this job: Join a dynamic team and make an impact in the fintech industry.
- Qualifications: 3-5 years of experience, expert in SQL and dbt, strong data quality knowledge.
- Other info: Collaborative environment with both on-site and remote work options.
The predicted salary is between 36000 - 60000 £ per year.
A leading financial technology company in the United Kingdom is seeking a skilled Analytics Engineer to transform raw data into business-ready datasets. You will collaborate with data engineers, scientists, and business stakeholders to implement data quality measures and create analytics solutions that scale with growth.
The ideal candidate has 3-5 years of experience, expert knowledge in SQL and dbt, and a strong understanding of data quality practices. This role supports both on-site and remote work arrangements.
Analytics Engineer - Build scalable data models (Remote) employer: Spendesk
Contact Detail:
Spendesk Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer - Build scalable data models (Remote)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and analytics solutions. This is your chance to demonstrate your expertise in SQL and dbt, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common analytics scenarios. Think about how you've tackled data quality issues in the past and be ready to discuss your approach with potential employers.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Analytics Engineer - Build scalable data models (Remote)
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 it in past projects, so don’t hold back on the details!
Talk About Data Quality: Since data quality is key for us, share examples of how you've implemented data quality measures in your previous roles. This will show us you understand its importance.
Collaborate Like a Pro: We love teamwork! Mention any experiences where you’ve collaborated with data engineers, scientists, or business stakeholders. It’ll help us see how you fit into our culture.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and keep everything organised. We can’t wait to hear from you!
How to prepare for a job interview at Spendesk
✨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 common SQL problems can really help you stand out.
✨Showcase Your Data Quality Knowledge
Since data quality is a key part of the role, be ready to talk about your experience with data quality measures. Think of specific examples where you implemented these practices and the impact they had on your projects.
✨Familiarise Yourself with dbt
If you have experience with dbt, make sure to highlight it! If not, take some time to learn the basics and understand how it integrates with analytics workflows. Being able to discuss its benefits will show your commitment to the role.
✨Prepare for Collaboration Questions
As you'll be working with various teams, expect questions about collaboration. Think of times when you worked with data engineers or business stakeholders, and be ready to share how you navigated challenges and achieved results together.
