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 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, enterprise data lake/lakehouse implementations, and Informatica integration solutions. Candidates should have between 5 to 10 years of relevant experience and a strong technical background in data engineering within enterprise environments.

Key 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 platforms such as Denodo, Starburst, and/or Dremio.
- Develop secure, governed, and scalable data pipelines aligned with enterprise standards.
- Support both 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.

Required Qualifications
- Proven experience with Apache Spark (PySpark and/or Scala Spark).
- Hands-on knowledge of Apache Iceberg.
- Expertise in Informatica Data Integration solutions.
- Familiarity with MinIO Object Storage.
- Experience with Denodo platform for data virtualization.
- Strong skills in SQL and data modeling.
- Solid understanding of data warehousing concepts.
- Proficient in ETL/ELT development processes.
- Experience using Git for version control.

Preferred Qualifications
- Experience with Starburst and/or Dremio platforms.
- Knowledge of data governance and metadata management practices.
- Familiarity with data quality frameworks.
- Understanding of CI/CD pipelines for data workflows.
- Programming skills in Python.
- Experience with Kafka or other streaming technologies.
- Knowledge of lakehouse architecture patterns.
- Prior involvement in enterprise data lake and lakehouse implementations.
- Ability to perform performance tuning and optimization of large-scale data workloads.

This role offers the opportunity to work on cutting-edge data platforms and contribute to the development of scalable, secure, and efficient data solutions within a dynamic enterprise environment. Candidates with a strong technical foundation and a passion for data engineering are encouraged to apply.