CTG is seeking a Data Engineer for a client project to design and deliver modern lakehouse solutions that support enterprise analytics and data-driven decision-making. The role focuses on building scalable data pipelines, implementing Microsoft Fabric lakehouse architectures, and developing Spark/PySpark solutions that integrate data from multiple enterprise systems. Responsibilities include designing, developing, and supporting enterprise data engineering solutions with Microsoft Fabric; building scalable lakehouse architectures with proper schema design and data organization; developing Spark Notebooks and Spark/PySpark applications for ingestion, transformation, and processing; orchestrating reliable data pipelines from diverse source systems; managing file structures, metadata, and storage in lakehouse environments; implementing security, permissions, and governance across Fabric workspaces; optimizing processing performance and troubleshooting production issues; collaborating with architects, analysts, and business stakeholders; participating in Agile development processes, code reviews, testing, and CI/CD deployments; and contributing to the ongoing improvement of data engineering standards and best practices. Requirements include 5+ years in Data Engineering or related fields; strong hands-on experience with Microsoft Fabric (lakehouse design, Spark Notebook development, schema design, file structure management, security/access control); Spark/PySpark development; experience building and orchestrating enterprise data pipelines; integrating data from multiple sources

CTG is seeking a Data Engineer for a client project to design and deliver modern lakehouse solutions that support enterprise analytics and data-driven decision-making. The role focuses on building scalable data pipelines, implementing Microsoft Fabric lakehouse architectures, and developing Spark/PySpark solutions that integrate data from multiple enterprise systems. Responsibilities include designing, developing, and supporting enterprise data engineering solutions with Microsoft Fabric; building scalable lakehouse architectures with proper schema design and data organization; developing Spark Notebooks and Spark/PySpark applications for ingestion, transformation, and processing; orchestrating reliable data pipelines from diverse source systems; managing file structures, metadata, and storage in lakehouse environments; implementing security, permissions, and governance across Fabric workspaces; optimizing processing performance and troubleshooting production issues; collaborating with architects, analysts, and business stakeholders; participating in Agile development processes, code reviews, testing, and CI/CD deployments; and contributing to the ongoing improvement of data engineering standards and best practices. Requirements include 5+ years in Data Engineering or related fields; strong hands-on experience with Microsoft Fabric (lakehouse design, Spark Notebook development, schema design, file structure management, security/access control); Spark/PySpark development; experience building and orchestrating enterprise data pipelines; integrating data from multiple sources