Data Engineer

Data Engineer Employment Type: Full-Time Work Location: KSA Experience Required: Hands-on experience with Spark development, Informatica integration solutions, and enterprise data platforms.

Responsibilities

• Design and develop scalable data ingestion and transformation pipelines.
• Build, optimize, and maintain Spark-based ETL/ELT workloads.
• Develop and manage data models and datasets using Apache Iceberg tables.
• Implement and support data integration workflows using Informatica.
• Enable analytics and data consumption through Denodo, Starburst, and/or Dremio.
• Develop secure, governed, and scalable data pipelines aligned with enterprise standards.
• Support batch and near real-time data processing requirements.
• Implement data quality, metadata management, and validation controls.
• Collaborate with Platform Engineers on deployment, integration, and operationalization activities.
• Support migration, testing, and production rollout initiatives.
• Troubleshoot and optimize data pipeline performance, reliability, and scalability.

Requirements

• 5 to 10 Role Overview We are looking for a Data Engineer to build, configure, and optimize data ingestion, transformation, and consumption workloads on a modern on-premises lakehouse platform.
• The ideal candidate will have strong hands-on experience with Spark-based development, enterprise data lake/lakehouse implementations, and Informatica-based integration solutions.
• Apache Spark (PySpark and/or Scala Spark) Apache Iceberg Informatica Data Integration MinIO Object Storage Denodo SQL and Data Modeling Data Warehousing Concepts ETL/ELT Development Git Version Control Good-to-Have Skills Starburst and/or Dremio Data Governance and Metadata Management Data Quality Frameworks CI/CD for Data Pipelines Python Kafka or Streaming Technologies Lakehouse Architecture Patterns Experience with enterprise data lake and lakehouse implementations Performance tuning and optimization of large-scale data workloads