Department: Insurance Retail

Location: North West UK - Hybrid

Compensation: £40,000 - £45,000 / year

Description

We’re seeking an Intermediate Data Engineer to join our Insurance Retail department, supporting development squads with reliable, automated, and cloud-ready data solutions. This role is suited to someone who can combine strong SQL, scripting, and AWS experience with modern DevOps practices to build, maintain, and improve data pipelines, data services, and supporting infrastructure.

AI is a key part of the role. You will be expected to use AI-assisted engineering tools responsibly to accelerate development, improve documentation, support analysis, and identify opportunities to automate repeatable data engineering and operational tasks. Working closely with engineers, analysts, architects, and stakeholders, you will help turn data requirements into maintainable, observable, and secure solutions.

You will maintain awareness of industry and technology developments, contribute to technical discussions, and support continuous improvement across data engineering, automation, and operational practices. The role includes ownership of work throughout its lifecycle, from development and testing through to production support, incident resolution, continuous improvement, and knowledge sharing across the department.

About CDL

CDL is one of the UK’s leading software development houses, employing over 600 people at its campus in Stockport. It has a consistent history in the high-volume retail insurance sector. CDL has spearheaded developments in the aggregator, web, and telematics space, including connected home, enrichment, and self-service solutions. As a result, the company’s robust and innovative technologies have enabled its customers to thrive in the highly competitive UK insurance marketplace.

We have built a collaborative and creative culture, leveraging AI-driven solutions to enhance our products, processes, and decision-making. We pride ourselves on cultivating an inspiring working environment with our employees at the heart of our company.

In a nutshell, we are the market-leading software house in our industry, creating the software, websites, and apps for the Insurance & Finance sector across the UK. If you were to go on a price comparison website, approximately 65% of the companies on there are our clients!

What You'll Do

• Building, testing, monitoring, and maintaining data pipelines and infrastructure to support the Data Platform using best practices including CI/CD, IaC, and DevOps.
• Apply security best practices across data pipelines, cloud infrastructure, and operational processes, ensuring data is protected through appropriate access controls, encryption, monitoring, and secure engineering practices.
• Use AWS services and PostgreSQL/AWS RDS knowledge to design, deliver, and support scalable, reliable, and secure data solutions, ensuring appropriate governance, resilience, and protection of business data.
• Actively embrace AI-assisted engineering practices and demonstrate a willingness to learn, experiment with, and responsibly adopt emerging AI tools such as Kiro, GitHub Copilot, or equivalent technologies to improve delivery flow, quality, documentation, analysis, and operational efficiency.
• Develop and maintain automated deployment, testing, and operational workflows using GitLab pipelines, version control, Terraform/OpenTofu, and scripting.
• Contribute to data quality, lineage, governance, and observability practices to ensure data is trusted, traceable, secure, and supportable throughout its lifecycle.
• Investigate data quality, platform reliability, pipeline performance, and operational issues, identifying practical improvements, preventative actions, and automation opportunities that enable squads to move faster and more safely.
• Working with business stakeholders, analysts, and architects to understand business and technical requirements, designing data models and data structures that support reporting, analytics, and operational use cases.
• Contribute to database and data platform activities such as upgrades, data migrations, schema updates, and platform modernisation initiatives.
• Documenting processes and products, sharing knowledge across the squad and wider business, and supporting the development of less experienced engineers through mentoring, pairing, or technical guidance where appropriate.
• Contribute significantly to small-to-medium feature deliveries and multi-person initiatives, collaborating with engineers and stakeholders to deliver reliable outcomes.