They’ve reached the point where reporting can’t just be powered by clever people knowing where to look.
The business needs a proper analytical layer. Clean models, agreed definitions, trusted Power BI datasets and fewer arguments over whose number is right.
You’ll be the most senior technical Analytics Engineer in the team, owning how data is modelled, structured and made usable for analysts, reporting teams and senior stakeholders.
The work sits close to the business.
You’ll be asking how things are counted, why teams measure things differently, what should become a shared metric, and how to build that into something reusable rather than another one-off query.
What you’ll be doing
* Owning the analytical / semantic data layer
* Designing clean, reusable models for reporting and analytics
* Defining business metrics and making sure they are used consistently
* Building trusted Power BI datasets and semantic models
* Creating documentation so analysts and stakeholders know what they are using
* Improving data quality, governance and reporting consistency
* Guiding analysts on SQL, modelling, query structure and best practice
* Acting as the bridge between engineering, analytics and the business
What they’re looking for
* Strong SQL
* Good Power BI experience, especially datasets / semantic models
* Experience modelling data for analytics, reporting or BI
* Strong understanding of data modelling principles, ideally Kimball / semantic modelling
* Experience working directly with business stakeholders to define metrics and resolve inconsistencies
* Someone comfortable taking messy business questions and turning them into clean, reusable data structures
The bigger thing is being able to bring order to data that a lot of people depend on.
You’ll suit this if you like the modelling, definition and structure side of analytics as much as the output people see at the end.
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