Data Engineer

EXPERIENCE

• Minimum 10 years in Data Engineering Domain
• Experience in UAE or Middle East is desirable

EDUCATION

• Bachelor's Degree in Information Technology or a related field

KEY SKILLS

• Strong hands-on experience with Cloudera Data Platform (CDP) and modern Data Lakehouse architectures.
• Expertise in SQL, Python, and data pipeline development for large-scale data integration and transformation.
• Experience with Talend, Apache Spark, Kafka, and Airflow for batch, real-time, and streaming data processing.
• Strong knowledge of Trino, Delta Lake/Iceberg, and Delta Sharing for data virtualization, storage, and sharing.
• Experience in data modelling, including Dimensional, Data Vault, and Lakehouse modelling techniques, Medallion Architecture and Data Mesh principles.
• Hands-on experience with OpenMetadata, Apache Ranger, metadata management, data lineage, and data governance frameworks.
• Experience in API integration, data services, and enterprise data product development.
• Proficiency in Git, CI/CD, DevOps practices, and performance optimization.

Nice-to-Have Skills

• Machine Learning Data Engineering and Feature Stores.
• Power BI Semantic Models and Analytics Enablement.
• Docker and Kubernetes.

• Strong experience working with Linux-based operating systems (RHEL, CentOS, Rocky Linux, Ubuntu).
• Cloud platforms (Azure, AWS, or GCP).

BEHAVIORAL COMPETENCIES

• Analytical Thinking & Problem Solving
• Accountability & Ownership

• Collaboration & Stakeholder Management
• Innovation & Continuous Improvement

FUNCTIONAL COMPETENCIES

Analysis Data Engineering & Integration
Design, development, and optimization of scalable ETL/ELT pipelines, data ingestion frameworks, and data processing solutions.

Data Platform & Architecture
Strong understanding of Data Lakehouse architecture, Medallion Architecture, Data Products, Data Modeling, and enterprise data platform best practices.

Data Governance & Security
Implementation of metadata management, data lineage, data quality, access control, and governance frameworks to ensure trusted and secure data assets.

Platform Operations & Performance Optimization
Monitoring, troubleshooting, automation, capacity management, and performance tuning of data platforms, pipelines, and query engines.