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- Tasks: Design data models and deliver insights for product teams using SQL and modern data pipelines.
- Company: Dynamic financial tech company in Greater London with a focus on innovation.
- Benefits: Hybrid work model, competitive bonuses, personal development budget, and mental health support.
- Why this job: Shape products with trusted data and make a real impact in the fintech space.
- Qualifications: Strong SQL skills and experience with dbt and data governance.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 50000 - 65000 £ per year.
A financial technology company in Greater London is hiring an Analytics Engineer to design robust data models and deliver insights for product teams. The role requires strong SQL skills and experience with modern data pipelines, particularly using dbt. You will work cross-functionally to ensure data governance and support analytics workflows.
The company offers a hybrid work model, competitive bonuses, and a generous benefits package, including a personal development budget and mental health support.
Hybrid Analytics Engineer — Shape Product with Trusted Data employer: Flagstone
Contact Detail:
Flagstone Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Hybrid Analytics Engineer — Shape Product with Trusted Data
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. It’s all about making connections that can help us get our foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL projects and data models. This gives us a chance to demonstrate our expertise and stand out from the crowd.
✨Tip Number 3
Prepare for the interview by brushing up on common analytics questions and scenarios. We should be ready to discuss how we’ve tackled data challenges in the past.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure our application gets noticed and shows we’re genuinely interested in the role.
We think you need these skills to ace Hybrid Analytics Engineer — Shape Product with Trusted Data
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 can design robust data models and deliver insights, so don’t hold back on showcasing your experience with SQL and any relevant projects you've worked on.
Talk About Your Data Pipeline Experience: If you've got experience with modern data pipelines, especially using dbt, let us know! We’re keen to hear about how you’ve implemented these tools in past roles and how they’ve helped you support analytics workflows.
Cross-Functional Collaboration is Key: This role involves working closely with product teams, so share examples of how you've collaborated across different functions. We love seeing candidates who can bridge the gap between technical and non-technical teams!
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 get to know you better. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Flagstone
✨Master Your SQL Skills
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss your experience with writing complex queries and how you've used SQL to derive insights from data in previous roles.
✨Showcase Your Data Pipeline Experience
Familiarise yourself with modern data pipelines, especially dbt. Be ready to explain how you've designed or worked with data models and how they’ve impacted product teams. Real-world examples will make your experience stand out.
✨Understand Data Governance
Since the role involves ensuring data governance, be prepared to discuss your understanding of data quality, compliance, and best practices. Think about how you've contributed to maintaining data integrity in past projects.
✨Emphasise Cross-Functional Collaboration
This position requires working closely with various teams. Prepare to share examples of how you've successfully collaborated with product teams or other departments to deliver insights and drive decisions based on data.