Data Engineer

Datamatics Technologies; Riyadh Region; On-site; SAR 223,000 - 446,000; Full time

Job summary

Datamatics Technologies is seeking a Data Engineer to design and optimize data ingestion, transformation, and consumption workloads on an on-premises lakehouse platform in Saudi Arabia. You will work with Spark-based ETL/ELT, Iceberg tables, and Informatica data integration, enabling analytics through Denodo, Starburst, and Dremio.

The role requires hands-on Spark, Iceberg, and Informatica experience, with strong SQL/data modeling skills, and a focus on scalable, governed data pipelines.

Qualifications

• Hands-on experience with Spark development and lakehouse platforms.
• Experience with Informatica Data Integration and metadata controls.
• Proficiency in SQL, data modeling, and data warehousing concepts.
• Experience with object storage (MinIO) and data virtualization (Denodo).
• Exposure to modern data pipeline tooling and CI/CD for data workloads.

Responsibilities

• Design and develop scalable data ingestion and transformation pipelines.
• Build and optimize Spark-based ETL/ELT workloads.
• Model data and manage datasets with Iceberg tables.
• Implement and support data integration workflows using Informatica.
• Enable analytics via Denodo, Starburst, or Dremio.
• Develop secure, governed, and scalable data pipelines.
• Support batch and near real-time processing and data quality controls.
• Collaborate with Platform Engineers on deployment and ops activities.
• Assist migrations, testing, and production rollout; troubleshoot pipelines.

Skills

Spark

Iceberg

Informatica

MinIO

Denodo

SQL/Data Modeling

Data Warehousing

ETL/ELT Development

Git

Tools

Starburst

Dremio

Kafka

CI/CD for Data Pipelines

Python

Job description

Job Description – Data Engineer

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

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.

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 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.

Must-Have Skills

• 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