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# Senior Analytics Engineer

- **Company:** RSK Group
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £50,000.0 - £80,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Business Intelligence Development, Cloud Database, Performance Tuning, Power BI, SQL Databases, Snowflake, Information Technology, Star Schema
- **Published:** September 16, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5885195899

## About the Role

A relevant degree (e.g. computer science, engineering, mathematics) or equivalent practical experience.

Substantial analytics engineering or BI development experience, including time in a senior or lead role owning a transformation and metrics layer.

Expert SQL, including performant queries and the design of well-structured, maintainable data models.

Expert DBT - macros, packages, testing, documentation and CI - with a track record of keeping a large model estate clean.

Deep Power BI experience: semantic/data modelling, DAX, performance tuning, and building reports people actually trust.

Experience with cloud data warehouses; exposure to Snowflake is highly desirable.

Strong grasp of dimensional modelling (star schema), metric layer design and ELT best practice.

Demonstrable experience defining and governing business metrics across multiple business units, including navigating disagreement about definitions.

## Description

Take technical ownership of the DBT transformation layer on our Snowflake warehouse - its architecture, standards, modularity, testing and documentation.

Own the certified metrics layer: one agreed definition per group metric, drillable by business and division, documented and version-controlled.

Broker metric definitions with the business - getting autonomous operating companies to a single, defensible way of counting, and holding the line once it is agreed.

Lead the design of Power BI semantic models and datasets so that reporting is fast, reliable and genuinely self-serve.

Extend certified coverage as new businesses are connected, so that group numbers describe more of the group rather than a subset of it.

Rationalise the reporting estate - consolidate and retire low-value assets, and make the ongoing maintenance cost of a new asset explicit before it is built.

Make data quality visible: quality and coverage indicators on the reporting itself, and a route for recurring issues to move from flagged to automatically resolved.


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