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For Companies At a Glance
- Tasks: Design and build innovative data pipelines and scalable architecture for a new data platform.
- Company: Fast-growing tech-first insurer with a collaborative and ambitious team.
- Benefits: Competitive salary, bonus, flexible hybrid working, and influence on tech direction.
- Why this job: Shape the future of data science and ML in a greenfield environment.
- Qualifications: 5+ years as a Data Engineer with strong SQL, Python, and Databricks skills.
- Other info: Join a small team where your work directly impacts decision-making.
The predicted salary is between 51000 - 85000 £ per year.
Data Engineer – MGA (Greenfield Build)
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 already working in data engineering. Attend meetups or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks, SQL, and Python. Having tangible examples of your work can really set you apart when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss how you've built data pipelines or worked with large datasets. Practice common interview questions and think about how you can demonstrate your stakeholder engagement experience.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly shows your enthusiasm and commitment to joining 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 our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about building a new data platform and how your past experiences make you the perfect fit for our ambitious team. Let your personality come through!
Showcase Your Projects: If you've worked on relevant projects, whether in a professional or personal capacity, be sure to include them. We love seeing real examples of your work, especially if they involve building data pipelines or scalable systems.
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 you’re keen to join 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 set you apart.
✨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.
✨Engage with Stakeholders
Since the role involves client-facing conversations, practice articulating complex technical concepts in a way that’s easy for non-technical stakeholders to understand. This will show your strong communication skills and ability to collaborate effectively.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data landscape and future projects, especially around data science and ML initiatives. This not only shows your interest but also helps you gauge if the role aligns with your career goals.
