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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 impactful projects.
- Why this job: Join a greenfield build 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 folks in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insider info that could help you stand out.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving Databricks, SQL, and Python. 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 data pipelines or integrating systems, and be ready to discuss your past experiences in detail.
✨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 and engaged with our platform.
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Databricks, SQL, and Python, and don’t forget to mention any previous work on greenfield projects. We want to see how your skills align with what we're building!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and explain why you're excited about joining our ambitious team. Let us know how you can contribute to shaping our data landscape from the ground up.
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's building data pipelines or implementing data quality frameworks, we love seeing real examples of your work that demonstrate 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 to join our team!
