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- Tasks: Build robust data pipelines and conduct complex SQL analysis for impactful insights.
- Company: Leading data-driven company in Greater London with a focus on innovation.
- Benefits: Flexible hours, hybrid work options, and extensive health benefits.
- Why this job: Join a dynamic team and make a real difference through data insights.
- Qualifications: Experience with BI tools and strong SQL skills required.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
A leading data-driven company in Greater London is looking for a data professional to build robust data pipelines and conduct complex SQL analysis. This role involves working with cross-functional teams to provide insights through data modelling and dashboards.
Candidates should have experience with BI tools and a strong SQL background.
The company offers competitive benefits, including flexible hours, hybrid work opportunities, and extensive health benefits.
Analytics Engineer — Flexible Hours, Pipelines & Insights employer: MVF
Contact Detail:
MVF Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer — Flexible Hours, Pipelines & Insights
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, SQL analyses, and any dashboards you've built. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Practice common SQL queries and be ready to discuss your experience with BI tools. We want you to feel confident and ready to impress!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Analytics Engineer — Flexible Hours, Pipelines & Insights
Some tips for your application 🫡
Show Off Your SQL Skills: Make sure to highlight your SQL experience in your application. We want to see how you've used SQL to solve problems or create insights in your previous roles. Don't be shy—give us some examples!
Talk About Teamwork: Since this role involves working with cross-functional teams, share any experiences where you collaborated with others. We love to see how you can communicate and work effectively with different departments.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your experience and skills. Avoid fluff—let your qualifications shine!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at MVF
✨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 Pipeline Experience
Be ready to talk about your experience building data pipelines. Think of specific examples where you’ve successfully implemented a pipeline, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Familiarise Yourself with BI Tools
Since the role involves working with BI tools, make sure you’re familiar with the ones mentioned in the job description. If you have experience with specific tools, be prepared to discuss how you’ve used them to create dashboards or provide insights.
✨Prepare for Cross-Functional Collaboration Questions
This role requires working with cross-functional teams, so think about times when you’ve collaborated with others. Prepare examples that highlight your communication skills and how you’ve contributed to team success through data insights.
