Data Engineer - Insurance
£80,000
1 Year FTC
London Based - 2/3 days in Office
We’re looking for a Mid Data Engineer to help design, build, and operate scalable, reliable, and high-quality data infrastructure across a modern Microsoft-based data platform.
This role sits at the intersection of software engineering and data management, ensuring that data flows seamlessly from source systems into analytics-ready structures that power insight, reporting, and decision-making across the organisation.
You’ll play a key role in shaping how data is built, trusted, and consumed—working closely with business domains, analysts, data scientists, and platform engineers.
Data Engineering & Pipelines
1. Build and maintain robust ETL/ELT pipelines using Microsoft Fabric (Data Factory, Lakehouse, etc.)
2. Design reliable ingestion processes from APIs, databases, and file-based sources
3. Apply best-practice pipeline design patterns for resilience and re-runnability
Data Modelling & Analytics Enablement
4. Design analytical data models that are performant, maintainable, and business-friendly
5. Apply dimensional modelling techniques for BI and reporting use cases
6. Build and optimise Power BI semantic models and datasets
Microsoft Data Platform
7. Contribute to the evolution of a modern Azure/Microsoft data platform
8. Optimise pipelines for performance, scalability, and cost efficiency
9. Work confidently across cloud data storage and compute services
Data Mesh & Domain Ownership
10. Support domain-oriented data product development in partnership with business teams
11. Promote standards for naming, metadata, documentation, and discoverability
12. Enable decentralised data ownership while maintaining consistency
Experience
13. Proven experience as a Data Engineer in a modern cloud data environment
14. Strong SQL skills (complex queries, joins, optimisation)
15. Hands-on Python for data processing and pipeline development
16. Experience with Microsoft Fabric and Power BI (datasets, semantic models)
17. Understanding of data modelling for analytics and reporting
18. Familiarity with CI/CD, testing, version control, and data quality practices
19. Exposure to data mesh / domain-oriented data ownership (desirable)