Analytics Engineer

Role Overview

The Analytics Engineer will be part of the IS Data & Analytics team, responsible for data transformation & modelling, data quality & reliability, stakeholder enablement, and engineering practice. The role will involve designing, building, and maintaining data models and Power BI semantic models across the bronze, silver, and gold layers in Microsoft Fabric, using SQL (dbt) and notebooks.

What You Will Do

Key responsibilities include writing tests to check data quality and integrity, fixing data problems, collaborating with data scientists, data analysts, and business analysts to understand data requirements, and transforming raw data into actionable insights.

Why It Might Be a Fit

To be considered for this role, the ideal candidate will have 3–5 years of experience in analytics engineering, data engineering, or BI / data warehouse work, with experience delivering at least two full-cycle data analytics projects.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or any related discipline.
• 3–5 years of experience in analytics engineering, data engineering, or BI / data warehouse work, with experience delivering at least two full-cycle data analytics projects
• Strong SQL skills and a good understanding of data modelling (star schemas, fact and dimension tables, slowly changing dimensions)
• Hands-on Microsoft Fabric across the medallion architecture (Lakehouse, Warehouse, Dataflow Gen2, notebooks) or a similar tool such as Databricks, Synapse, or Snowflake with dbt.
• Semantic models & DAX for Power BI (measures, relationships, row-level security)
• Software engineering practice: Git for version control, peer review, using CI/CD pipelines, and producing modular, reusable code
• Turning business needs into clear, documented metric/KPI definitions and data contracts, and into scalable analytics solutions
• Clear communication, in writing and speaking, with both technical and business stakeholders