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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 career growth opportunities.
- Why this job: Join a greenfield project and shape the future of data science and ML.
- Qualifications: 5+ years as a Data Engineer with strong SQL and Python skills.
- Other info: Small, ambitious team with high visibility and influence on tech direction.
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 working in data engineering or at companies you're interested in. A friendly chat can lead to insider info and even job referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks, SQL, and Python. 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 knowledge and soft skills. Be ready to discuss your experience with building data pipelines and engaging with stakeholders. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. 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 you've worked on 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 how you've designed and deployed data pipelines or worked with large-scale datasets, and don’t forget to mention your enthusiasm for joining a greenfield project!
Showcase Your Stakeholder Engagement Skills: Since excellent stakeholder engagement is key for this role, include examples in your application that demonstrate your ability to communicate effectively with both technical and non-technical teams. We want to see how you can bridge the gap between analytics and business needs.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, we love seeing applications come in through our own platform!
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 working closely with analytics and business teams, be ready to talk about your experience in client-facing situations. Share how you’ve successfully engaged stakeholders in the past and how you can ensure their needs are met through your data solutions.
✨Emphasise Collaboration
This position is all about being part of a small, ambitious team. Highlight your experience in collaborative environments and how you’ve influenced tech direction in previous roles. Show that you’re not just a lone wolf but someone who thrives in a team setting.
