Senior Data Quality Engineer

Contract Duration

Visa Requirements

• Preference will be given to candidates who:
• Hold a UAE Golden Visa
• Hold a UAE Freelance Visa
• Can self-sponsor and obtain their own work permit

About the Role

Key Responsibilities

• Develop and execute data quality and profiling solutions using Python and IBM technologies.
• Implement and maintain enterprise-grade data quality rules, controls, and monitoring frameworks.
• Work with IBM Cloud Pak for Data (CP4D) to support data ingestion, transformation, and governance workflows.
• Design and optimize ETL pipelines using IBM DataStage for batch ingestion and data processing.
• Ensure data consistency, accuracy, and integrity across enterprise data warehouse environments using IBM DB2 Warehouse.
• Collaborate with data architects, engineers, and governance teams to define and enforce data standards.
• Support metadata management and data cataloging initiatives using IBM Watson Knowledge Catalog (WKC).
• Develop and maintain logical and physical data models aligned with enterprise architecture standards.
• Create and maintain data architecture documentation and governance artifacts.

• IBM Watson Knowledge Catalog (WKC)

• Metadata management and data governance practices
• Data cataloging, lineage, and stewardship concepts

Data Quality & Profiling

• Python (including Jupyter/Notebook environments)
• IBM Cloud Pak for Data (CP4D)
• IBM DataStage (ETL and batch data processing)
• IBM QualityStage
• Data profiling, cleansing, validation, and monitoring techniques
• Data quality rule development and implementation

• IBM DB2 Warehouse

• Data transformation and pipeline development
• Enterprise-scale data integration experience
• ETL/ELT design and optimization

• IBM InfoSphere Data Architect

• Logical and physical data modeling
• Erwin Data Modeler (including reverse engineering)
• Data architecture documentation and standards

Preferred Qualifications

• Experience working in large enterprise data environments.
• Strong understanding of data governance, master data management, and metadata frameworks.
• Knowledge of data quality metrics, controls, and monitoring best practices.
• Experience supporting regulatory, audit, or compliance-driven data initiatives.
• Strong analytical, problem-solving, and stakeholder management skills.