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Data Engineer - Datamatics Technologies
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Location
In office (Karachi)
Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 15, 2026.
Overview
Company
Impact
Profile match
Datamatics Technologies is a technology services company providing enterprise data and AI services, cloud engineering, cybersecurity and managed platform services, along with business process outsourcing and talent augmentation. Its open roles are concentrated in Pakistan and Saudi Arabia, in Karachi, Islamabad, Lahore, Riyadh, Dammam and Jubail, with further positions in India, Sweden, Finland and Poland, and it offers data governance, analytics, cloud migration, managed SOC and agile delivery and testing services. It hires data and platform engineers, Kafka and Azure cloud engineers, database administrators, Power BI developers, RPA engineers, IAM consultants and GenAI technical leads.
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
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