Data Analytics Engineer

Requirements

Must have:

- Strong hands-on experience with dbt Core (modelling, testing, documentation) - Skilled in building models for on-prem Microsoft SQL Server (MSSQL) - Excellent SQL skills with a focus on performance optimisation - Solid Python experience in data or analytics engineering contexts - Comfortable working in Git-based, collaborative engineering environments - Strong understanding of data warehousing, dimensional modelling, ELT/ETL - Clear communicator with strong documentation habits - Ability to work closely with non-technical stakeholders - Experience in the insurance or financial services industry is preferred - Nice to have experience with BI tools (Power BI, etc.) - Exposure to CI/CD for analytics engineering - Familiarity with data governance and security concepts

Responsibilities:

- Build, test, and maintain analytics models using dbt Core, ensuring data accuracy and reliability - Create comprehensive dbt tests and documentation to support transparency and quality - Collaborate with the team through Git-based workflows (branches, PRs, code reviews) - Partner with analysts to convert business needs into scalable, production-ready data models - Develop and maintain dbt models on on-prem MSSQL environments - Use Python for data transformation, automation, and workflow improvements - Uphold data quality, modular design, and analytics engineering best practices - Continuously optimise data pipelines and support enhancements to the wider analytics infrastructure

Company:

We are a large insurance company undergoing meaningful data modernisation, looking for a skilled Analytics Engineer to join our high-performing, engineering-led data team in a hybrid London location. This position is initially a 6-month contract with strong potential for extension, allowing you to influence core data models used across the business.