Eden Scott
Senior Analytics Engineer

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
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
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
-
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


Get help with your application
Your very own career expert that helps elevate your application to the next level.
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.
Interested?
Get in touch to find out more about the role, the business and what they’re looking to build.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London