Power BI Data Engineer

As a Power BI Data Engineer in Enterprise Analytics, your role involves designing, developing, and maintaining interactive Power BI dashboards and reports to empower business stakeholders with actionable insights. Key Responsibilities: - Build and optimize ETL pipelines for data ingestion, transformation, and loading into analytics platforms such as Power BI, Snowflake, Databricks, or Microsoft Fabric. - Develop and implement star schemas, data models, and semantic models for analytics cubes to support enterprise reporting and BI needs. - Collaborate with data scientists, analysts, and business teams to translate requirements into scalable data solutions. - Ensure data quality, governance, and security across all BI workflows, adhering to best practices. - Deploy and monitor data solutions on cloud platforms, preferably Azure, with AWS/GCP knowledge being a plus. - Continuously improve the performance of data pipelines and reports through optimization and automation. Qualifications: - 5-7 years of experience in data engineering, focusing on BI solutions and Power BI development. Required Skills: - Strong expertise in Power BI (DAX, Power Query, report design) and building intuitive, high-performance dashboards. - Proven experience in designing and implementing ETL processes and star schemas for analytics cubes. - Hands-on experience with cloud data platforms like Snowflake, Databricks, or Microsoft Fabric. - Proficiency in SQL for querying and transforming large datasets. - Familiarity with Azure data services (e.g., Azure Data Factory, Synapse Analytics) or equivalent cloud tools. - Self-motivated with a proactive approach to problem-solving, capable of managing complex projects with minimal oversight. Preferred Skills: - Familiarity with data orchestration tools (e.g., Apache Airflow, Prefect). - Knowledge of data warehousing concepts and tools (e.g., Fabric, Redshift, BigQuery). - Exposure to AI/ML integration for predictive analytics or anomaly detection.,