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- Tasks: Design and build analytical data models using dbt and Snowflake for impactful insights.
- Company: Join Aviva, a leader in insurance, driving innovation through data.
- Benefits: Flexible work environment with 50% remote options and competitive pay.
- Other info: Collaborative team culture with opportunities for professional growth.
- Why this job: Transform raw data into actionable insights that drive business decisions.
- Qualifications: Strong SQL skills and experience with dbt and data modelling techniques.
The predicted salary is between 50000 - 65000 £ per year.
About the Company: Aviva is investing in its strategic data platform to unlock actionable insights across Insurance Claims.
Job Type: Contract - 6 Months
Location: NR1 3NG (50% office based 50% from home)
About the Role: Randstad Sourceright is recruiting on behalf of Aviva. We are seeking an experienced Analytics Engineer to design, build, and maintain high-quality analytical data models using dbt and Snowflake, supporting key Claims use cases across Motor, Property, and other Lines of Business. This role sits at the intersection of data engineering, BI, and business understanding—transforming raw operational data into trusted, governed datasets that enable reporting, self-service analytics, and advanced insight generation.
Responsibilities:
- Design and implement scalable analytical data models in Snowflake using dbt, following best practices including dimensional modelling, Slowly Changing Dimensions (SCDs), and incremental processing.
- Transform complex Claims source data into business-ready datasets aligned with agreed metrics and definitions.
- Own and evolve models that underpin dashboards, management information (MI), regulatory reporting, and ad-hoc analysis.
- Collaborate with business and technical teams to understand requirements and deliver actionable data solutions.
- Maintain documentation, testing, and quality standards to ensure data reliability and consistency.
Qualifications:
- Strong SQL skills and experience building analytical models in Snowflake.
- Hands-on experience with dbt, including models, tests, documentation, and incremental strategies.
- Solid understanding of data modelling techniques, such as Kimball-style dimensions, facts, and Slowly Changing Dimensions.
- Experience handling large, complex datasets in an enterprise environment.
- Excellent problem-solving, collaboration, and communication skills, with the ability to explain complex data concepts to business stakeholders.
Required Skills:
- Strong SQL skills
- Experience with dbt
- Data modelling techniques
- Handling large datasets
- Problem-solving and communication skills
Preferred Skills:
- Experience in an enterprise environment
Data Modelling (dbt/snowflake) in Wolverhampton employer: Aviva
Contact Detail:
Aviva Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modelling (dbt/snowflake) in Wolverhampton
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews by practising common questions and scenarios related to data modelling and analytics. We suggest doing mock interviews with friends or using online platforms to get comfortable with articulating your skills.
✨Tip Number 3
Showcase your work! If you’ve built any cool data models or projects, make sure to have them ready to share. We love seeing real examples of your skills in action, so don’t be shy about flaunting your achievements.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for talented individuals who can bring their expertise in dbt and Snowflake to our team.
We think you need these skills to ace Data Modelling (dbt/snowflake) in Wolverhampton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role. Highlight your experience with dbt and Snowflake, and don’t forget to showcase your SQL skills. We want to see how your background aligns with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data modelling and how your skills can help us at Aviva. Keep it concise but impactful—show us what makes you unique!
Showcase Relevant Projects: If you’ve worked on any relevant projects, make sure to mention them! Whether it’s building analytical models or transforming complex datasets, we love to see real-world examples of your work that demonstrate your expertise.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy—just follow the prompts and you’ll be all set!
How to prepare for a job interview at Aviva
✨Know Your Tools Inside Out
Make sure you’re well-versed in dbt and Snowflake. Brush up on your SQL skills and be ready to discuss how you've used these tools in past projects. Being able to explain your experience with dimensional modelling and Slowly Changing Dimensions will show that you know your stuff.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in the past. Think about specific situations where you transformed raw data into actionable insights. This will demonstrate your analytical thinking and ability to deliver solutions that meet business needs.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You’ll likely need to collaborate with non-technical stakeholders, so being able to break down your work into understandable language is key. Consider role-playing with a friend to refine your communication style.
✨Understand the Business Context
Familiarise yourself with Aviva’s business model and the specific claims processes they deal with. Knowing how your role as an Analytics Engineer fits into their broader goals will help you tailor your responses and show that you’re genuinely interested in contributing to their success.