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For Companies At a Glance
- Tasks: Design and build innovative data pipelines and scalable reporting systems.
- Company: Fast-growing tech-first insurer with a collaborative culture.
- Benefits: Competitive salary, bonus, flexible hybrid working, and influence on tech direction.
- Why this job: Join a greenfield project and shape the future of data science initiatives.
- Qualifications: 5+ years as a Data Engineer with strong SQL and Python skills.
- Other info: Small team environment offering autonomy and support.
The predicted salary is between 51000 - 85000 £ per year.
Location: London (Hybrid – typically 1–2 days per month in office)
Package: £85k base + 15% bonus
The Opportunity
Our Client is building a brand-new data platform from the ground up for a fast-growing, tech-first insurer. You’ll be joining a small but ambitious team and will play a pivotal role in shaping their entire data landscape, from infrastructure and pipelines to reporting and future data science initiatives.
The roadmap includes:
- Building sophisticated reporting solutions for the business
- Productionising algorithms into scalable reporting systems
- Laying the foundations for data science and ML initiatives already in the pipeline
Key Responsibilities
- Design, test, and deploy robust data pipelines for ingestion, transformation, and integration
- Build out scalable lakehouse architecture with Databricks
- Partner with analytics and business teams to deliver fit-for-purpose datasets
- Productionise algorithms into reporting systems
- Implement data quality and validation frameworks
- Create and maintain clear technical documentation
- Shape best practices and influence tech direction in a collaborative team environment
Skills & Experience
Essential:
- Proven experience (5+ years) as a Data Engineer, ideally building new platforms from scratch
- Hands-on with Databricks, dbt, and Azure data services
- Strong SQL and Python skills
- Track record of working with large-scale datasets and pipelines
- Excellent stakeholder engagement – comfortable in client-facing conversations
Desirable:
- Previous Insurtech or FinTech experience
- Certifications in Databricks or Azure Data Engineering (bonus)
Why Join?
- Greenfield build – huge influence on tech stack and direction
- High visibility – your work directly impacts decision-making
- Future-facing roadmap – exposure to data science & ML projects
- Small, collaborative team – autonomy with support
- Competitive package – £85k base + 15% bonus + flexible hybrid working
Sound like you? Apply now!
Data Engineer – MGA (Greenfield Build) employer: Arthur Recruitment
Contact Detail:
Arthur Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer – MGA (Greenfield Build)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at companies you're interested in. 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 or GitHub repository showcasing your projects, especially those related to data pipelines and architecture. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common data engineering questions and scenarios. Think about how you'd tackle building a data platform from scratch and be ready to discuss your thought process.
✨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 Data Engineer – MGA (Greenfield Build)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your hands-on experience with Databricks, SQL, and Python, as well as any relevant projects that showcase your ability to build data platforms from scratch.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this Data Engineer role. Share specific examples of your previous work, especially in building robust data pipelines and collaborating with teams, to show how you can contribute to our greenfield project.
Showcase Your Technical Skills: Don’t just list your technical skills; demonstrate them! If you have certifications in Databricks or Azure Data Engineering, mention them. Also, consider including links to any relevant projects or GitHub repositories that highlight your expertise.
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 this exciting opportunity. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Arthur Recruitment
✨Know Your Tech Stack
Make sure you’re well-versed in Databricks, dbt, and Azure data services. Brush up on your SQL and Python skills too, as these will likely come up during technical discussions. Being able to demonstrate your hands-on experience with these tools will show that you're ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've designed and deployed data pipelines or built platforms from scratch. Think about challenges you faced and how you overcame them. This will highlight your ability to contribute to their greenfield build effectively.
✨Engage with Stakeholders
Since this role involves client-facing conversations, practice articulating complex technical concepts in a way that’s easy for non-technical stakeholders to understand. Show that you can bridge the gap between tech and business needs, which is crucial for delivering fit-for-purpose datasets.
✨Be Ready to Discuss Future Trends
Familiarise yourself with current trends in data science and machine learning, especially as they relate to the insurance sector. Be prepared to share your thoughts on how these technologies can be integrated into their roadmap, demonstrating your forward-thinking mindset and enthusiasm for innovation.
