Intermediate Data Engineer

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 & 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.