Intermediate Data Engineer

Who you are

• Hold, or be willing to obtain, a relevant AWS certification that can be registered against the CDL APN
• Proven experience working with AWS services relevant to data engineering and operational support, such as RDS, S3, Lambda, ECS, EC2, VPC, CloudWatch and related services
• Experience with MySql and Oracle databases would be advantageous
• Strong SQL skills, including PostgreSQL experience, query optimisation awareness and the ability to investigate data or performance issues
• Good understanding of security principles including least-privilege access, encryption, secrets management, vulnerability remediation and secure handling of sensitive data
• Experience with CI/CD pipelines, automated testing and deployment practices using GitLab or similar tooling
• Experience with Infrastructure as Code tools such as Terraform, OpenTofu or CloudFormation
• Good understanding of version control workflows, branching strategies and GitLab best practice
• Experience of, or a strong willingness to learn, AI-assisted engineering tools such as Kiro, GitHub Copilot or similar technologies to improve engineering effectiveness and delivery outcomes
• Familiarity with observability and troubleshooting tooling such as Dynatrace, OpenSearch/Elasticsearch or CloudWatch logs
• Ability to communicate clearly, analyse problems, work collaboratively and explain technical concepts to both technical and non-technical stakeholders
• Familiarity with Agile methodologies and operational tooling such as Jira and ServiceNow

What the job involves

• 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
• 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

The application process

• This role's hiring manager: Jed Shaw
• This Policy was last updated in August 2026
• Applied
• Review
• Initial Screening Call (30 Mins)
• Teams Interview
• Final Interview
• Formal Offer
• Background Checks
• Hired

Benefits

• Hybrid working – occasional requirements to attend the office
• Flexible hours
• 25 days holiday to start, increasing by 1 day per 1 year of service up to 30 days
• Excellent training and development platform
• Opportunities for career progression
• Health and Wellbeing programme
• Virtual activities, lunch and learns, coffee mornings and meetups
• Life and health assurance
• Established Recognition Award System
• Great Parental Benefits
• Diversity and Inclusion network
• Pension scheme
• Community projects and volunteer days
• Refer a friend bonus