We are seeking a skilled Data Engineer to join our team in Saudi Arabia on a full-time basis. The successful candidate will be responsible for building, configuring, and optimizing data ingestion, transformation, and consumption workloads on a modern on-premises lakehouse platform. This role requires hands-on experience with Spark development, Informatica integration solutions, and enterprise data platforms. Candidates should have between 5 to 10 years of relevant experience and a strong background in Spark-based development, enterprise data lake/lakehouse implementations, and Informatica-based integration.
Key Responsibilities
- Design and develop scalable data ingestion and transformation pipelines to support enterprise data needs.
- Build, optimize, and maintain Spark-based ETL/ELT workloads ensuring high performance and reliability.
- Develop and manage data models and datasets utilizing Apache Iceberg tables for efficient data storage and retrieval.
- Implement and support data integration workflows using Informatica to enable seamless data movement and transformation.
- Facilitate analytics and data consumption through platforms such as Denodo, Starburst, and/or Dremio.
- Develop secure, governed, and scalable data pipelines aligned with enterprise data standards and policies.
- Support both batch and near real-time data processing requirements to meet diverse business needs.
- Implement data quality, metadata management, and validation controls to ensure data integrity and compliance.
- Collaborate closely with Platform Engineers on deployment, integration, and operationalization of data solutions.
- Assist with migration, testing, and production rollout initiatives to ensure smooth transitions and minimal disruption.
- Troubleshoot and optimize data pipeline performance, reliability, and scalability to maintain efficient data flow.
Required Qualifications
- Proficient in Apache Spark development, including PySpark and/or Scala Spark.
- Experience with Apache Iceberg for data modeling and management.
- Hands-on expertise in Informatica Data Integration solutions.
- Familiarity with MinIO Object Storage systems.
- Knowledge of Denodo platform for data virtualization and consumption.
- Strong skills in SQL and data modeling techniques.
- Solid understanding of data warehousing concepts and best practices.
- Proven experience in ETL/ELT development processes.
- Competent in using Git for version control and collaborative development.
Preferred Qualifications
- Experience with Starburst and/or Dremio data query engines.
- Knowledge of data governance frameworks and metadata management practices.
- Familiarity with data quality frameworks and implementation.
- Understanding of CI/CD pipelines for data engineering workflows.
- Proficiency in Python programming language.
- Experience with Kafka or other streaming technologies for real-time data processing.
- Understanding of lakehouse architecture patterns and enterprise data lake implementations.
- Skills in performance tuning and optimization of large-scale data workloads.
This role offers the opportunity to work with cutting-edge data technologies within a dynamic enterprise environment. The ideal candidate will be a proactive problem solver with a passion for building robust, scalable data solutions that drive business insights and operational efficiency.