Our client is a telecom company based in Oman that is implementing a centralized Data Management Hub to enhance data governance, integration, and analytics capabilities across the organization.

To ensure effective delivery of the Data Management Hub, they are looking for a Data Engineer (QA) to work in Muscat and support them for 12 months.

The role is 100% on-site.

The Data Engineer (QA-focused) is responsible for validating, testing, and monitoring data pipelines and warehouse/lakehouse environments. This role emphasizes quality assurance over development, ensuring that all data delivered to business users and analytics platforms meets defined standards.

Key Responsibilities

• Data Quality Assurance:
• Design and implement automated data validation and reconciliation processes
• Develop test cases for ETL pipelines, data ingestion, and transformation logic
• Perform root cause analysis for data discrepancies and anomalies
• Testing & Monitoring:
• Conduct unit, integration, and regression testing for ETL workflows and data models
• Monitor data pipelines for failures, performance bottlenecks, and data drift
• Implement alerting mechanisms for data quality issues
• Collaboration:
• Work closely with the Senior ETL Architect to validate pipeline logic and transformations
• Partner with business analysts to ensure data meets reporting and analytics requirements
• Provide feedback to developers on data quality improvements and bug fixes
• Documentation & Standards:
• Maintain QA documentation including test plans, test cases, and defect logs
• Contribute to establishing data quality standards and best practices
• Support compliance with governance, security, and privacy policies

Professional background

• Bachelor’s degree in computer science, Data Engineering, or related field
• 4–6 years of experience in data engineering, with at least 2 years in QA/testing roles
• Proficiency in SQL for data validation and reconciliation
• Hands-on experience with ETL tools (e.g., Informatica, Talend or similar)
• Familiarity with big data frameworks (Apache Spark, Databricks) and MPP platforms (Greenplum, Netezza etc)
• Knowledge of QA methodologies (unit testing, regression testing, automation frameworks)
• Familiarity with CI/CD pipelines, version control (Git), and infrastructure-as-code (Terraform, CloudFormation)
• Experience with JIRA and Confluence is highly desirable