We are looking for a skilled Power BI Developer with strong experience in designing data models, dashboards, and reports using Power BI and Azure-based data platforms. This role focuses on transforming complex datasets from Databricks Delta Lake and Azure data sources into high‑performance, insightful analytics that support business decision-making.
Key Responsibilities:
Design, develop, and maintain Power BI dashboards and reports aligned with business requirements
Build and optimise semantic data models in Power BI Desktop
Develop and manage DAX measures, calculated columns, and KPIs
Integrate Power BI with Databricks Delta Lake, Azure SQL, and other enterprise data sources
Collaborate with data engineers to understand ETL logic, data pipelines, and transformations
Validate and reconcile data across multiple sources to ensure data accuracy and integrity
Optimise report performance through model optimisation, aggregation tables, and query folding
Implement and manage Row-Level Security (RLS) and workspace access controls
Publish, schedule, and manage content in Power BI Service
Work closely with stakeholders to gather requirements and translate them into technical solutions
Provide documentation, support, and ongoing enhancements to Power BI solutions
Required Skills & Experience:
Proven hands-on experience with Power BI (Desktop & Service)
Advanced knowledge of DAX and SQL (mandatory)
Strong experience working with large datasets and enterprise data models
Solid understanding of data warehousing concepts (facts, dimensions, star schema)
Experience integrating Power BI with Databricks / Delta Lake or similar big data platforms
Good Understanding Of:
Data pipelines and ETL processes
Incremental refresh and Power BI refresh strategies
Partitioning and performance optimisation techniques
Data quality, validation, and governance principles
Azure ecosystem including Azure Data Factory, Azure SQL, and Databricks
Nice to Have:
Experience with Apache Spark / PySpark
Knowledge of Power BI deployment pipelines and DevOps practices
Exposure to Python for data analysis or automation
