Data Engineer

Datamatics Technologies; Riyadh; On-site; SAR 240,000 - 360,000; Full time

Job summary

Datamatics Technologies is seeking a Data Engineer to build and optimize data ingestion, transformation, and consumption workloads on a modern on-prem lakehouse platform in KSA. Strong Spark, Iceberg, and Informatica expertise are required to implement scalable data pipelines.

You will work with Denodo, SQL, and data modeling to enable analytics and governance across enterprise standards, with emphasis on batch and near real-time processing.

Qualifications

• Hands-on Spark development experience and lakehouse workloads.
• Experience with Informatica Data Integration and data pipelines.
• Proficiency with Apache Iceberg tables and data modeling concepts.
• Knowledge of MinIO storage, Denodo data virtualization, and SQL.
• Familiarity with data warehousing concepts and ETL/ELT processes.
• Version control using Git in a collaborative environment.

Responsibilities

• Design and develop scalable data ingestion and transformation pipelines.
• Build and optimize Spark-based ETL/ELT workloads.
• Manage data models and datasets using Iceberg tables.
• Implement and support Informatica integration workflows.
• Enable analytics through Denodo, Starburst, or Dremio.
• Ensure data quality, governance, and metadata management.
• Collaborate with Platform Engineers on deployment and operations.
• Support batch and near real-time data processing and migrations.

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

Denodo

Starburst

Dremio

Kafka

Job description

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