Power BI Developer/Data Engineer

Qualifications and Requirements 1.5–3 years of relevant experience in Power BI development, data engineering, business intelligence, or a related field. Hands-on experience developing dashboards and reports using Microsoft Power BI. Basic to intermediate knowledge of ETL processes and data integration concepts. Experience in data modeling and transforming data for reporting and analytics. Proficiency in Power Query and DAX. Working knowledge of SQL for querying, extracting, and manipulating data. Understanding of relational databases, data structures, and data quality principles. Strong analytical and problem-solving skills. Good attention to detail and the ability to validate data accuracy. Effective communication and collaboration skills. Ability to manage tasks independently while working with cross-functional teams. Preferred Qualifications Familiarity with Microsoft Excel and other data analysis tools. Exposure to Microsoft SQL Server, Azure data services, or cloud-based data platforms. Basic understanding of data warehousing, data pipelines, and dimensional modeling. Experience with scheduled data refreshes and Power BI Service. Knowledge of dashboard design principles and data visualization best practices. Key Responsibilities Design, develop, and maintain ETL processes to extract, transform, and load data from various sources. Create, develop, and maintain interactive dashboards and reports using Microsoft Power BI. Build and optimize data models in Power BI to support accurate and efficient reporting. Develop data transformations and calculations using Power Query and DAX. Connect Power BI to various data sources and ensure data accuracy, consistency, and reliability. Perform data cleansing, validation, and transformation to ensure high-quality reporting outputs. Optimize dashboard performance, data models, and report refresh processes. Collaborate with business users, analysts, and stakeholders to understand reporting requirements and translate them into effective BI solutions. Troubleshoot data integration, ETL, dashboard, and reporting issues. Maintain technical documentation for data pipelines, data models, dashboards, and reporting processes. Ensure data security, consistency, and adherence to established data governance standards. Support the continuous improvement of existing dashboards, reports, and data workflows.