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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 shape the future of insurance.
- Qualifications: Strong SQL skills and experience with dbt and data modelling techniques.
The predicted salary is between 50000 - 60000 £ 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 Coventry employer: Aviva
Contact Detail:
Aviva Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modelling (dbt/snowflake) in Coventry
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and projects using dbt and Snowflake. 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 SQL and data modelling techniques. Be ready to discuss how you've transformed complex datasets into actionable insights, as this is key for roles like the one at Aviva.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Modelling (dbt/snowflake) in Coventry
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 talk about specific models you've built or challenges you've faced will show your expertise.
✨Understand the Business Context
Since this role involves transforming data for business use, take some time to understand Aviva's insurance claims process. Familiarise yourself with key metrics and how they relate to the data models you'll be working on. This will help you demonstrate your ability to align technical solutions with business needs.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving skills, especially around handling large datasets and data modelling techniques. Think of examples where you’ve successfully tackled complex data issues and be ready to explain your thought process clearly.
✨Showcase Your Collaboration Skills
This role requires working closely with both technical and business teams. Be prepared to discuss how you've collaborated in the past, particularly in translating technical concepts for non-technical stakeholders. Highlight any experiences where your communication made a difference in project outcomes.