Data Analyst – Microsoft Power BI Job

Role Overview

The position is an exciting opportunity for a self-starter who enjoys working in a fast-paced, quality-oriented, and team environment.

What You Will Do

Responsible for understanding the existing data structure and tables, gathering and understanding business requirements, and supporting the end-to-end analytics lifecycle.

Why It Might Be a Fit

Empowered to create a career that will take you to where you want to go while working in an inclusive team environment.

Requirements

• Minimum 8 years of experience within this field.
• Strong hands-on experience designing and supporting complex enterprise Power BI solutions, including dashboards, reports, semantic models, and advanced analytics.
• Advanced expertise in SQL, DAX, semantic/data modeling, data engineering, and ETL/ELT, including performance optimization and integration of multiple enterprise data sources.
• Strong focus on AI-ready data preparation and modeling, ensuring data and semantic models are structured, governed, and optimized for traditional BI as well as AI-assisted and conversational analytics.
• Hands-on experience with Generative AI and prompt engineering to accelerate data preparation, SQL/DAX development, semantic modeling, report development, analysis, testing, troubleshooting, and documentation.
• Ability to develop future-ready, prompt-driven BI solutions, enabling natural-language interaction with governed enterprise data and analytics.
• Experience administering and supporting Power BI workspaces, reports, semantic models, refreshes, gateways, security, and production workloads.
• Strong Microsoft Fabric experience preferred, including data engineering, OneLake, Lakehouse/Warehouse, pipelines, semantic models, and Power BI.
• Experience modernizing and migrating on-premises SSAS models to Microsoft Fabric, with an emphasis on scalable, governed, and AI-ready architecture.
• Capable of supporting the end-to-end analytics lifecycle, from data ingestion and engineering through modeling, visualization, AI enablement, deployment, administration, and production support.

Tagged as: Data Analysis, Power BI, SQL