A Data Engineer with Power BI expertise designs, builds, and maintains scalable data pipelines and analytical solutions, transforming raw data into actionable insights. Key responsibilities include creating advanced Power BI dashboards (DAX, modeling), optimizing ETL processes, ensuring data quality, and collaborating with stakeholders. Required skills include SQL, Data Warehousing, Azure, Python/R, and 2–7+ years of experience. Key Responsibilities Data Modeling & Visualization: Develop interactive Power BI dashboards, reports, and KPIs, including complex DAX measures, row-level security (RLS), and data modeling. Pipeline Development (ETL): Design, build, and maintain data pipelines (using tools like Azure Data Factory, Python) to extract, transform, and load data from various sources into data warehouses. Database Management: Write complex SQL queries, optimize database performance, and work with relational/non-relational databases (SQL Server, Snowflake). Collaboration & Analysis: Translate business requirements into technical specifications, and work with Data Science and Engineering teams to support analytical needs. Support & Optimization: Enhance existing BI systems, troubleshoot data-related issues, and ensure data integrity. Qualifications & Skills Experience: 2–9 years of experience, with specific, hands-on experience in Power BI development. Power BI: DAX, Power Query, Data Modeling. SQL: High proficiency in DDL/DML. Data Warehousing: Knowledge of Snowflake, Redshift, or similar. Languages: Python or R for data manipulation. Soft Skills: Strong analytical thinking, problem-solving, and communication skills to work with stakeholders. Common Educational Background Bachelor's or Master's degree in Computer Science, Data Analytics, Engineering, or a related field. #J-18808-Ljbffr