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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analyst (Analytics Engineer) - **Company:** LegalAndGeneral - **Location:** Cardiff, UK - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Data Validation, Data Transformation, Python (Programming Language), Modular Design, Power BI, Cloud Services, SQL Databases, Test Data, Scripting, Snowflake, Git, Data Analytics, Software Version Control, Data Pipelines - **Published:** June 7, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=2545d1c48379c4fd ## About the Role Do you have experience in Scripting?, * Strong experience with SQL and data modelling (e.g. dimensional modelling, semantic modelling) * Experience with modern data transformation tooling (e.g. dbt strongly preferred) * Experience working with cloud data platforms (e.g. Snowflake, Azure, AWS) * Experience building and maintaining scalable data pipelines and datasets * Understanding of data quality, testing and governance practices * Experience working with Power BI datasets/semantic models (rather than solely report development) * Experience with Python or scripting for automation desirable * Exposure to version control (e.g. Git) and collaborative development practices ## Description We're looking for an Analytics Engineer to join our Data & Analytics team, helping to build scalable, reliable and well-governed data products using modern analytics engineering practices. This role is centred on data modelling, transformation and pipeline development, with a strong focus on dbt-style workflows and cloud data platforms (e.g. Snowflake). You'll play a key role in shaping how data is structured and delivered across the organisation, enabling high-quality, self-service analytics. While the role includes exposure to Power BI, the focus is on engineering robust datasets and semantic models that underpin reporting, rather than building dashboards. What you'll be doing: Build scalable data models and transformation layers * Design and develop reusable, well-structured data models to support analytics use cases * Apply best practices in dimensional modelling and semantic layer design * Build data transformation workflows using modern tools (e.g. SQL, dbt or equivalent) Develop and operate data pipelines * Create and maintain automated ELT pipelines to transform and deliver data from multiple sources * Ensure pipelines are reliable, efficient and scalable within a cloud data environment (e.g. Snowflake) * Promote standardisation, modular design and reusability across data transformations Drive data quality and engineering best practice * Implement testing frameworks (e.g. data validation, schema tests, lineage) to ensure data accuracy * Maintain documentation, version control and structured development practices * Contribute to the adoption of modern analytics engineering standards across the team Enable downstream analytics (Power BI) * Develop and maintain datasets and semantic models for Power BI consumption * Validate and test data within Power BI to ensure consistency with underlying models * Support programmatic interaction with Power BI (e.g. metadata extraction, automation, integration with data workflows) * Ensure strong alignment between upstream models and downstream reporting outputs Collaborate with analysts and stakeholders * Translate business requirements into scalable, reusable data assets * Enable self-service analytics by delivering clean, well-structured datasets * Work closely with analysts to improve data usability and consistency Optimisation and continuous improvement * Improve performance of queries, transformations and data models * Identify opportunities to automate processes and enhance efficiency * Contribute to tooling, frameworks and shared development patterns ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) ## Related Articles - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary Germany](https://www.wearedevelopers.com/magazine/277-data-analyst-salary-germany) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london) - [Data Analyst Salary in Switzerland](https://www.wearedevelopers.com/magazine/276-data-analyst-salary-in-switzerland)