Data Engineer

Job Description – Data Engineer

Employment Type: Full-TimeWork Location: KSAExperience Required: Hands-on experience with Spark development, Informatica integration solutions, and enterprise data platforms.Years of experience: 5 to 10Role OverviewWe 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.Key ResponsibilitiesDesign and develop scalable data ingestion and transformation pipelinesBuild, optimize, and maintain Spark-based ETL/ELT workloadsDevelop and manage data models and datasets using Apache Iceberg tablesImplement and support data integration workflows using InformaticaEnable analytics and data consumption through Denodo, Starburst, and/or DremioDevelop secure, governed, and scalable data pipelines aligned with enterprise standardsSupport batch and near real-time data processing requirementsImplement data quality, metadata management, and validation controlsCollaborate with Platform Engineers on deployment, integration, and operationalization activitiesSupport migration, testing, and production rollout initiativesTroubleshoot and optimize data pipeline performance, reliability, and scalabilityMust-Have SkillsApache Spark (PySpark and/or Scala Spark)Apache IcebergInformatica Data IntegrationMinIO Object StorageDenodoSQL and Data ModelingData Warehousing ConceptsETL/ELT DevelopmentGit Version ControlGood-to-Have SkillsStarburst and/or DremioData Governance and Metadata ManagementData Quality FrameworksCI/CD for Data PipelinesPythonKafka or Streaming TechnologiesLakehouse Architecture PatternsExperience with enterprise data lake and lakehouse implementationsPerformance tuning and optimization of large-scale data workloads