Data Engineer

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 designing, building, and optimizing data ingestion, transformation, and consumption processes on a modern on-premises lakehouse platform. This role requires hands-on experience with Spark development, Informatica integration solutions, and enterprise data platforms. The ideal professional will have between 5 to 10 years of relevant experience and a strong background in Spark-based ETL/ELT workloads and data lakehouse implementations.

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 using Apache Iceberg tables to support efficient data storage and retrieval.
- Implement and maintain data integration workflows leveraging Informatica solutions.
- Facilitate analytics and data consumption by enabling platforms such as Denodo, Starburst, and/or Dremio.
- Develop secure, governed, and scalable data pipelines that comply with enterprise standards and policies.
- Support both batch and near real-time data processing requirements to meet diverse business needs.
- Implement data quality checks, metadata management, and validation controls to ensure data integrity.
- Collaborate closely with Platform Engineers on deployment, integration, and operationalization of data solutions.
- Assist with migration, testing, and production rollout activities to ensure smooth transitions and minimal downtime.
- Troubleshoot and optimize data pipeline performance, scalability, and reliability to maintain operational excellence.

Required Qualifications

- Proven experience with Apache Spark, including PySpark and/or Scala Spark development.
- Strong knowledge of Apache Iceberg for data modeling and dataset management.
- Hands-on expertise with Informatica Data Integration tools.
- Familiarity with MinIO Object Storage systems.
- Experience working with Denodo for data virtualization and consumption.
- Proficiency in SQL and data modeling techniques.
- Solid understanding of data warehousing concepts and architecture.
- Extensive experience in ETL/ELT development and pipeline design.
- Competency in using Git for version control and collaboration.

Preferred Qualifications

- Experience with Starburst and/or Dremio platforms for data querying and analytics.
- Knowledge of data governance frameworks and metadata management practices.
- Familiarity with data quality frameworks and implementation strategies.
- Understanding of CI/CD processes tailored for data pipelines.
- Programming skills in Python for automation and scripting tasks.
- Exposure to Kafka or other streaming technologies for real-time data processing.
- In-depth knowledge of lakehouse architecture patterns and enterprise data lake implementations.
- Proven ability 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. Candidates with a passion for data engineering and a commitment to delivering high-quality, scalable data solutions are encouraged to apply.