Overview

Power BI - Data Engineer Position: Power BI - Data Engineer Job Description: Power BI / Azure Data Engineer – Job Description Position : Power BI and Azure Data Engineer Job Summary We are looking for a skilled and detail-oriented Power BI / Data Analytics Engineer with 4–6 years of experience in business intelligence, data engineering, and cloud analytics platforms.

Responsibilities

• Design, develop, and maintain interactive dashboards, reports, and semantic models using Power BI.
• Create optimized data models, DAX calculations, KPIs, measures, Power Query transformations, and enterprise reporting solutions.
• Develop and maintain complex SQL queries, stored procedures, and database objects for analytics and reporting.
• Build and maintain scalable ETL/ELT pipelines using Azure Data Factory, Databricks (PySpark/SQL), and modern data integration frameworks.
• Develop Python scripts for automation, data processing, validation, and workflow optimization.
• Integrate data from multiple enterprise systems including SQL Server, Oracle, SAP, ERP, APIs, Azure platforms, and cloud data warehouses.
• Work with modern cloud platforms including Microsoft Azure, Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, and SQL Server.
• Design dimensional data models (Star Schema/Snowflake Schema) and publish curated datasets for enterprise analytics.
• Optimize Power BI reports through DAX optimization, query tuning, incremental refresh, aggregation, and performance best practices.
• Implement Row-Level Security (RLS), workspace governance, deployment pipelines, and Power BI Service administration.
• Collaborate with Data Engineering teams to design scalable Medallion Architecture (Bronze–Silver–Gold) and Lakehouse solutions.
• Support deployment, release management, CI/CD implementation, and migration across Development, UAT, and Production environments.
• Maintain technical documentation for dashboards, datasets, pipelines, and operational runbooks. Troubleshoot reporting, performance, data quality, and production issues while ensuring high availability of analytics solutions.