Senior Analytics Engineer

Eden Scott; Glasgow; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Eden Scott is recruiting a Senior Analytics Engineer in Glasgow for a growing SaaS business. Hybrid work arrangement. You will own the semantic layer, develop analytics-ready data models and drive self-service analytics across the organisation.

You will design semantic models, write complex SQL, build Power BI datasets, and collaborate with Data Engineering to leverage the data platform. AI readiness and governance are also part of the scope.

Qualifications

• Strong SQL skills and data modelling experience.
• Experience building semantic models and datasets.
• Proficiency with Power BI, DAX and M Query.

Responsibilities

• Build and own the semantic layer.
• Design and maintain semantic models and datasets.
• Develop analytics-ready data models using Kimball; ensure consistent metrics.
• Collaborate with Data Engineering to maximise the data platform.
• Write and optimise complex SQL; build Power BI datasets and models.
• Drive self-service analytics and reduce one-off reporting.
• Improve data governance, quality and documentation.

Skills

SQL

Power BI

DAX

Data Modelling

Kimball

Semantic Models

Tools

Power BI

Job description

Senior Analytics Engineer | Competitive Salary | Hybrid – Glasgow

We are working with a growing SaaS business where data is becoming a much bigger part of the product and wider business strategy.

They are now looking for a Senior Analytics Engineer to take ownership of the layer between their data platform and the people using that data across reporting, analytics and AI.

This isn’t a role focused purely on building dashboards. You will be working on the underlying models, metrics and standards that make data reliable and useful across the organisation.

What you will be doing

Build and own the semantic layer

Design and maintain well-structured semantic models and datasets

Develop business-ready data models using Kimball and star-schema principles

Make sure key metrics and definitions are consistent across the business

Work closely with the existing Data Engineering team to make the most of the underlying data platform

Develop analytics solutions

Write and optimise complex SQL

Build Power BI datasets, DAX measures and models

Turn business requirements into practical analytical solutions

Look for ways to move the business away from one-off reporting and towards self-service analytics

Improve how data is used

Identify repetitive reporting and analytical tasks that could be automated

Build solutions that reduce manual effort and improve consistency

Use tools such as Power Automate where they add real value

Help establish better standards around documentation, data quality and governance

Support the next stage of AI and analytics

AI is becoming an increasingly important part of the organisation's data strategy, so you’ll also have the opportunity to help prepare the data environment for things such as Copilot, AI agents and natural-language analytics.

That includes making sure models have the right business context, definitions and metadata, while being comfortable using AI tools yourself and, importantly, knowing when to challenge and validate what they produce.

Provide technical leadership

Set good practice around analytics engineering and data modelling

Mentor other members of the data and analytics team

Work with Data Engineering, Product and Commercial stakeholders

Help shape the longer-term approach to analytics across the organisation

What we are looking for

You’ll probably come from an Analytics Engineering, BI Development, Data Modelling or similar background, with strong experience working with data beyond simply producing reports.

You’ll have:

Strong SQL skills, including query optimisation

Solid experience with Power BI, DAX, M Query and data modelling

A good understanding of semantic models, star schemas and Kimball methodology

Experience creating trusted, governed data models and metrics

An understanding of data quality, lineage and documentation

Experience automating manual reporting or analytical processes

The ability to take a business problem and turn it into a sensible data solution

A practical approach to using AI tools, with the judgement to validate outputs before they make their way into production

It would be useful if you also have

Experience with Copilot, AI agents or natural-language analytics

Experience working with procurement, spend, supplier or other complex master-data environments

Experience mentoring or leading other analysts or Analytics Engineers

Exposure to Power Automate or similar workflow automation tools

Why this role?

This is a chance to have a genuine influence on how a growing SaaS business uses data.

You’ll be joining a capable Data Engineering function rather than being expected to do everything yourself, and you’ll have the opportunity to shape the models, metrics and standards that sit underneath the organisation’s reporting and analytics.

There’s also a real opportunity to help define how AI fits into the data landscape, rather than simply being asked to use the latest AI tool because everyone else is.

If you enjoy solving data problems properly, building things that other people can rely on, and having a say in how analytics should work, this could be a very interesting next step.