Data Engineer

Datamatics Technologies; Islamabad; Presencial; PKR 8.863.000 - 19.202.000; Jornada completa

Descripción de la vacante

Datamatics Technologies in KSA is seeking a Data Engineer to build, configure, and optimize data ingestion, transformation, and consumption workloads on a modern on-premises lakehouse platform. The role emphasizes hands-on Spark-based development and Informatica integration.

You will design scalable pipelines, implement data models with Iceberg, and enable analytics through Denodo, Starburst, or Dremio while ensuring data governance and reliability in enterprise environments.

Formación

• Hands-on experience with Spark-based development (PySpark/Scala).
• Proficient in Informatica Data Integration and data pipeline design.
• Strong SQL, data modeling, and warehousing concepts.
• Experience with lakehouse architectures and on‑premises platforms.

Responsabilidades

• Design and optimize scalable data ingestion and transformation pipelines.
• Develop and maintain Spark-based ETL/ELT workloads.
• Implement data models using Apache Iceberg and manage datasets.
• Enable analytics through Denodo, Starburst, or Dremio.
• Collaborate with Platform Engineers on deployment and operations.

Conocimientos

Spark

SQL

Data Modeling

ETL/ELT Development

Data Warehousing Concepts

Git Version Control

Herramientas

Apache Iceberg

Informatica Data Integration

MinIO Object Storage

Denodo

Starburst

Dremio

Descripción del empleo

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