Oscar
Data Engineer
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Data Engineer
Location: London (Hybrid)
Salary: £65,000 - £70,000 DOE
Industry: Insurance
The Opportunity
I'm currently working with an established insurance business that is looking to hire a Data Engineer to help modernise its data estate and develop a scalable, secure, cloud-based data platform.
This is a hands-on Data Engineering opportunity where you'll work across data, IT and business teams to modernise legacy systems, automate manual processes and improve the quality, accessibility and reliability of data across the organisation.
You'll play an important role in the continued development of the data platform, working with Microsoft Azure, SQL and Python to build and maintain data pipelines, integrate multiple data sources and deliver reliable solutions for operational and analytical use cases.
The role offers the opportunity to contribute to wider data transformation initiatives, influence technical and architectural decisions, and work closely with stakeholders across broking, finance, operations and compliance.
If you're a Data Engineer with strong SQL and Python skills, experience with Azure data technologies and an interest in cloud migration and platform modernisation, this could be an excellent opportunity.
Key Responsibilities
- Modernise legacy data processes and migrate services, workflows and infrastructure to scalable Microsoft Azure technologies.
- Design, build and maintain reusable ETL/ELT pipelines and data integrations.
- Integrate data from internal business systems, insurance and finance platforms, APIs, files and third-party sources.
- Develop data solutions using SQL, Python and Microsoft data technologies.
- Improve data quality, accessibility, performance, automation and operational resilience.
- Contribute to data architecture, cloud infrastructure and platform development decisions.
- Work with business stakeholders to understand requirements and translate them into practical technical solutions.
- Identify opportunities to automate manual processes and improve operational efficiency.
- Establish data validation, monitoring, documentation and governance standards.
- Ensure data solutions meet security, regulatory and GDPR requirements.
- Support reporting and analytics initiatives, including occasional input into Power BI.
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Essential Skills and Experience
- Proven experience as a Data Engineer or in a similar data engineering role.
- Strong SQL skills, including complex queries, stored procedures, transformations and performance optimisation.
- Strong Python skills for data processing, automation and integration.
- Hands-on experience building and maintaining ETL/ELT pipelines.
- Experience integrating APIs, file-based feeds and multiple business data sources.
- Experience with Microsoft Azure data technologies, such as Azure Data Factory, Azure SQL, Microsoft Fabric, Synapse Analytics or Data Lake technologies.
- Strong understanding of relational databases, data modelling and data warehouse design.
- Experience with Git-based version control and collaborative development practices.
- Understanding of CI/CD, automated deployment and technical documentation.
- Experience contributing to cloud migration, platform modernisation or wider data transformation projects.
- Strong problem-solving skills and the ability to communicate effectively with technical and non-technical stakeholders.
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Desirable
- Previous experience within insurance or financial services
- Familiarity with AI-assisted development tools and modern engineering practices.
Package and Benefits
- £65,000 - £70,000 salary (depending on experience)
- Annual bonus scheme
- Opportunity to contribute to the modernisation of an established insurance data estate.
- Hands-on exposure to Microsoft Azure and modern cloud data technologies.
- Opportunity to influence data architecture, engineering standards and platform development.
- Exposure to complex data across insurance, finance and wider business operations.
- Close collaboration with technical teams and business stakeholders.
- Opportunity to automate legacy processes and deliver meaningful improvements to data quality and accessibility.
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