Data Engineer (Power BI and SSIS)

Job Overview We are seeking a Data Engineer to support and advance the organization’s data-driven and self-service analytics strategy. This role is responsible for deg, building, and maintaining scalable data pipelines and data platforms that transform raw data into trusted, analytics-ready assets. The position plays a critical role in enabling enterprise reporting, governing Self-Service Intelligence SSI, and high-performance Power BI analytics. The successful candidate will work across hybrid data environments, ensuring data quality, reliability, security, and performance while empowering business users with timely and actionable insights. Key Responsibilities Design, develop, test, and maintain enterprise-grade data pipelines supporting analytics, reporting, and self-service BI use cases Build and optimize ETL and ELT workflows using SQL Server Integration Services SSIS, Azure Data Factory, and equivalent data integration tools Enhance and refactor existing SSIS packages to improve performance, scalability, and operational stability Integrate data from multiple internal and external data sources across on-premises and cloud environments Collaborate with business stakeholders, analysts, and data consumers to translate reporting and analytical requirements into production-ready data solutions Design and maintain data models, semantic layers, and certified datasets to support Power BI dashboards and self-service analytics consumption Implement data quality controls, validation rules, and monitoring mechanisms across data pipelines Support governed self-service analytics by delivering reusable, well-documented datasets that reduce dependency on IT teams Monitor, troubleshoot, and resolve data ingestion, transformation, and performance issues impacting reporting users Implement data warehousing structures, dimensional models, and performance-optimized schemas aligned with business usage patterns Maintain clear documentation of data flows, transformation logic, and architectural components Requirements Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline Minimum 3 years of hands-on experience in data engineering, BI engineering, or a closely related role Strong proficiency in SQL with solid experience in query optimization and performance tuning Hands-on experience with SQL Server Integration Services SSIS for enterprise ETL development Experience working with Microsoft data platforms including SQL Server and Power BI Practical experience enabling Self-Service BI or Self-Service Intelligence in enterprise environments Exposure to cloud platforms such as Azure, AWS, or GCP, including services like Azure Data Factory, Redshift, or BigQuery Good understanding of data warehousing concepts, dimensional modeling, and star schema design Knowledge of data governance, security, and compliance practices in enterprise or regulated environments Strong analytical mindset with the ability to communicate t