Analytics Engineer (Data Modelling)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Analytics Engineer (Data Modelling): Designing and building high-performing semantic models to support Power BI and Microsoft Fabric reporting with an accent on SQL optimization and logical data structuring. Focus on transforming complex datasets into clean, business-friendly analytical layers within an Amazon Redshift environment.
Location: Must be based in or able to commute to Leeds, UK (Hybrid: 2 days per week in office)
Compensation: £500–£550 per day (Outside IR35)
Company
is a recruitment and talent solutions provider connecting experienced professionals with specialized technical roles.
What you will do
- Design, build, and optimize semantic models for Power BI and Microsoft Fabric.
- Develop robust SQL-based transformations to create clear, business-friendly data structures.
- Improve the performance, scalability, and usability of reporting datasets.
- Apply advanced data modeling principles to ensure reliable analytical layers.
- Collaborate with data engineers to ensure effective model implementation on Amazon Redshift.
- Shape organizational data consumption by creating a trusted reporting foundation.
Requirements
- Must be able to work on-site in Leeds 2 days per week.
- Strong SQL development expertise with complex query optimization skills.
- Proven experience in designing and building semantic models and analytical data layers.
- Deep understanding of data modeling concepts for reporting and analytics.
- Experience working with complex datasets and translating business requirements into logical solutions.
- Experience supporting Power BI reporting through well-designed underlying models.
Nice to have
- Exposure to Microsoft Fabric.
- Experience with Amazon Redshift or broader AWS ecosystem.
Culture & Benefits
- 3-month contract duration with a strong possibility of extension.
- Outside IR35 engagement.
- Opportunity to work on high-impact data architecture within a complex organization.
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