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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 with high visibility and career growth opportunities.
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 on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your data engineering projects. 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 practising common data engineering questions and scenarios. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨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 passionate candidates who are eager to join our team!
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 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 looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you’re excited about building a new data platform and how your past experiences make you the perfect fit. Keep it engaging and relevant to the role.
Showcase Your Projects: If you’ve worked on any relevant projects, especially those involving large-scale datasets or data pipelines, make sure to include them. We love seeing real-world applications of your skills, so don’t hold back!
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. Plus, it’s super easy!
