Data Engineer

Datamatics Technologies LLC; Saudi Arabia; On-site; SAR 180,000 - 240,000; Full time

Job summary

Datamatics Technologies LLC is seeking a Data Engineer to design, implement, and optimize data ingestion, transformation, and consumption workloads on a modern on-premises lakehouse platform.

The candidate should have hands-on Spark development, expertise with Iceberg tables, and Informatica-based integration solutions to support enterprise data platforms and analytics requirements.

Qualifications

• Hands-on Spark development experience.
• Experience with iceberg-based data lake/lakehouse architectures.
• Proficiency in Informatica Data Integration.
• Familiarity with MinIO storage.
• Experience with Denodo for data virtualization.
• Strong SQL and data modeling skills.
• Understanding of data warehousing concepts.
• ETL/ELT development lifecycle.
• Version control with Git.

Responsibilities

• Design and develop scalable data ingestion and transformation pipelines.
• Build and optimize Spark-based ETL/ELT workloads.
• Develop and manage data models and datasets using Iceberg.
• Implement and support Informatica-based workflows.
• Enable analytics through Denodo, Starburst, or Dremio.
• Ensure secure, governed, scalable pipelines.
• Support batch and near real-time processing.
• Implement data quality, metadata, and validation controls.
• Collaborate with Platform Engineers on deployment and ops.

Skills

Apache Spark (PySpark/Scala)

Apache Iceberg

Informatica Data Integration

MinIO Object Storage

Denodo

SQL & Data Modeling

Data Warehousing Concepts

ETL/ELT Development

Git Version Control

Tools

Starburst

Dremio

Kafka

Python

CI/CD for Data Pipelines

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.
Years of experience: 5 to 10

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