BI Data Modeler
Job in
Glasgow, Glasgow City Area, G1, Scotland, UK
Listed on 2026-06-13
Listing for:
Eden Scott
Full Time
position Listed on 2026-06-13
Job specializations:
-
IT/Tech
Data Analyst, Data Engineering, Business Systems/ Tech Analyst, Data Science Manager
Job Description & How to Apply Below
Overview
Are you a data> who thrives on turning complex data into powerful, scalable insights? We are a high‑growth, market‑leading SaaS organization where data is at the heart of everything we do, powering critical insights, intelligent search and pricing capabilities for our global customer base. We are hiring a BI Data Modeller to help build the foundations of our next‑generation data platform, combining strong modelling expertise with AI‑driven analytics.
Responsibilities- Designing semantic models, datasets and metric layers used across BI & AI
- Building clean, governed data structures for self‑serve analytics
- Developing and optimizing SQL (views, stored procedures)
- Creating Power BI datasets, DAX measures and reports
- Using AI tools to accelerate development and improve efficiency
- Partnering with engineering & business teams to deliver scalable solutions
- Driving improvements in data quality, governance and automation
- 2+ years in data modelling, BI or analytics engineering
- Strong SQL and experience with Power BI (DAX, datasets, reporting)
- Solid understanding of star schema and Kimball modelling
- Experience building models for both reporting and advanced analytics
- Exposure to AI tools in analytics workflows
- Experience with automation tools (e.g., Power Automate) and repeatable data processes
- Passion for clean, structured relational data
- Work for a true market‑leader in SaaS
- Be at the forefront of AI‑powered analytics
- Shape how data is modelled, accessed and used across the business
- Join a team that values ownership, innovation and continuous improvement
You will challenge data problems, question assumptions (especially around AI outputs), enjoy building solutions that others rely on, and push the boundaries of modern analytics.
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