Data Analytics Engineer

ROLE:

You will be responsible for driving the business to make data-driven decisions and improving self-service Business Intelligence within the company. The role sits within a high-quality, well-governed data platform where strong foundations, clear ways of working, and rigorous engineering standards are already in place. You will be joining a team that takes real pride in what has been built, and your contribution will help maintain that standard while the platform takes on increasingly diverse and complex use cases. The role is a hybrid analytics engineering position, working across the full data stack from pipeline development and data modelling through to BI delivery and end-user enablement. You will serve as a critical bridge between the data platform and business users, owning the end-to-end delivery of data products and ensuring that what gets built is governed, high-quality, and genuinely useful to the business.



REQUIREMENTS:

* Strong Power BI proficiency - experience building and maintaining semantic models, reports, and dash-boards; experience with both direct query and import access control configurations; understanding of row-level security and workspace governance
* Data modelling - strong command of data modelling concepts including star schemas, semantic model design, and the medallion architecture (Bronze/Silver/Gold); ability to model from both a BI and data engi-neering perspective
* Analytics engineering - experience with dbt for building and maintaining data transformation pipelines using SQL; adherence to best practices including documentation, testing, and model structure
* Stakeholder communication - proven ability to engage business users, gather requirements, manage expectations, and translate technical concepts into accessible language; comfortable in meetings with senior stakeholders
* Data governance - understanding of access control, data quality standards, and platform governance principles



NICE TO HAVE:

* Experience with Databricks or similar cloud data platforms
* Experience with Azure cloud infrastructure
* Familiarity with ELT/ETL patterns and data table formats
* Experience with Infrastructure as Code, DevOps, or DataOps practices
* Familiarity with Dynamics 365 Finance and Operations