Job Summary
KEY ACCOUNTABILITIES EXPERIENCE Core Accountabilities • Design, build, and manage enterprise data products and datasets in accordance with data architecture, governance, security, and data-sharing standards. • Develop and maintain scalable data ingestion, integration, and transformation pipelines using batch, real-time, and streaming processing patterns. • Engineer and optimize data solutions across the enterprise data platform, ensuring performance, reliability, scalability, and reusability. • Design and maintain logical and physical data models to support analytics, AI, and business consumption. • Implement data quality, validation, monitoring, and observability frameworks to ensure trusted and reliable data assets. • Administer and support platform services, including orchestration, metadata management, data cataloging, lineage, and access controls. • Develop APIs, data virtualization, and data-sharing services to enable secure and efficient access to enterprise data. • Monitor, troubleshoot, and optimize platform operations, data pipelines, and resource utilization to ensure service availability and operational excellence. • Maintain technical documentation, standards, and operational runbooks to support governance, compliance, and knowledge transfer. • Collaborate with architects, data governance teams, data scientists, and business stakeholders to deliver scalable, governed, and business-aligned data solutions. • Drive automation, innovation, and adoption of modern data engineering practices to continuously improve platform capabilities and user experience. • Support platform upgrades, testing, deployment, and release activities to ensure successful delivery and operational readiness. Supporting Accountabilities • Comply with enterprise data management, information security, governance, and software development policies and procedures. • Participate in audits, compliance reviews, and assessments related to data platform operations and data governance. • Support the preparation of operational, service performance, and data quality reports, as required. • Identify and escalate data quality, security, compliance, and operational risks, recommending corrective actions where appropriate. • Support change, release, and environment management activities across development, testing, and production environments. • Support user onboarding, access provisioning, and knowledge-transfer activities to promote effective adoption of data platform services. • Contribute to continuous improvement initiatives that enhance operational efficiency, automation, and platform maturity
Key Responsibilities
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 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. Sr Data Engineer (Contractor) – Data & Analytics • 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). • 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