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- Tasks: Design and validate data models for enterprise initiatives in the insurance sector.
- Company: Join a leading firm in the London Market insurance industry.
- Benefits: Enjoy hybrid work options and competitive daily rates up to £644.
- Why this job: Be part of a dynamic team shaping data solutions that drive business success.
- Qualifications: Experience in data modeling and London Market insurance is essential.
- Other info: Contract role until 31/12/2025 with opportunities for professional growth.
The predicted salary is between 50000 - 90000 £ per year.
Duration: contract to run until 31/12/2025
Location: London, Hybrid 2-3 days per week onsite
Rate: up to £644 p/d Umbrella inside IR35
Role purpose / summary
We are seeking an experienced Data Modeller with proven expertise in the London Market insurance sector. The successful candidate will play a key role in designing and validating data models that support enterprise data initiatives. This includes working closely with data engineers, architects, and business stakeholders to ensure data structures are scalable, accurate, and aligned with business needs.
Key Skills/ requirements
- Design and maintain conceptual, logical, and physical data models to support reporting, analytics, and operational systems.
- Collaborate with data engineers and analysts to ensure models are implemented correctly and efficiently.
- Translate complex business requirements into scalable and maintainable data structures.
- Ensure data models comply with data governance, compliance, and London Market regulatory standards.
- Document data definitions, relationships, and lineage using industry-standard modeling tools.
- Support data quality initiatives by identifying gaps and inconsistencies in source systems and downstream usage.
Qualifications:
- London Market insurance experience is essential, including familiarity with market data structures and regulatory reporting.
- Strong experience in data modeling (conceptual, logical, physical) using tools such as Erwin, ER/Studio, or dbt.
- Solid understanding of data warehousing, data lakes, and enterprise data architecture.
- Proficiency in SQL and experience working with cloud data platforms (e.g., Azure, AWS, GCP).
- Familiarity with data governance frameworks, metadata management, and data cataloging tools.
- Excellent communication and documentation skills, with the ability to explain complex data concepts to non-technical stakeholders.
Preferred Skills:
- Experience with insurance platforms such as Guidewire, Duck Creek, or legacy PAS systems.
- Knowledge of Delta Lake, Apache Spark, and data pipeline orchestration tools.
- Exposure to Agile delivery methodologies and tools like JIRA, Confluence, or Azure DevOps.
- Understanding of regulatory data requirements such as Solvency II, Core Data Record (CDR), or Blueprint Two.
All profiles will be reviewed against the required skills and experience. Due to the high number of applications we will only be able to respond to successful applicants in the first instance. We thank you for your interest and the time taken to apply!
Data Modeler employer: Undisclosed
Contact Detail:
Undisclosed Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modeler
✨Tip Number 1
Network with professionals in the London Market insurance sector. Attend industry events or join relevant online forums to connect with potential colleagues and learn about the latest trends and challenges in data modelling.
✨Tip Number 2
Familiarise yourself with the specific data modelling tools mentioned in the job description, such as Erwin or dbt. Consider taking online courses or tutorials to enhance your skills and demonstrate your commitment to mastering these tools.
✨Tip Number 3
Prepare to discuss your experience with regulatory requirements like Solvency II or Core Data Record during interviews. Having concrete examples of how you've navigated these regulations in past roles will set you apart from other candidates.
✨Tip Number 4
Showcase your ability to communicate complex data concepts clearly. Practice explaining your previous projects to non-technical stakeholders, as this skill is crucial for collaborating with business teams and ensuring alignment on data initiatives.
We think you need these skills to ace Data Modeler
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in the London Market insurance sector. Emphasise your data modelling skills and any relevant tools you've used, such as Erwin or dbt.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the key skills mentioned in the job description. Explain how your background aligns with their needs, particularly your experience with data governance and regulatory standards.
Showcase Relevant Projects: Include examples of past projects where you designed and maintained data models. Detail your role in collaborating with data engineers and analysts to demonstrate your teamwork and communication skills.
Proofread Your Application: Before submitting, carefully proofread your application for any errors. Ensure that your language is clear and professional, and that you’ve adhered to any specific application instructions provided by the company.
How to prepare for a job interview at Undisclosed
✨Showcase Your London Market Experience
Make sure to highlight your experience in the London Market insurance sector during the interview. Discuss specific projects or roles where you designed data models that adhered to regulatory standards, as this will demonstrate your relevance to the position.
✨Demonstrate Technical Proficiency
Be prepared to discuss your expertise in data modelling tools like Erwin or dbt. You might be asked to explain how you've used these tools in past projects, so having concrete examples ready will help you stand out.
✨Communicate Complex Concepts Simply
Since you'll need to explain complex data structures to non-technical stakeholders, practice simplifying your explanations. Use analogies or straightforward language to convey your points clearly, showcasing your communication skills.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving abilities. Think of examples where you identified data quality issues or gaps in source systems and how you addressed them, as this will illustrate your analytical skills and attention to detail.
