Data Engineer

Position Summary

• Dicetek is seeking an accomplished Data Engineer to join our expanding technology team in Abu Dhabi.
• This full-time position requires a seasoned technical professional capable of designing, building, and scaling modern cloud data pipelines and data warehousing architectures.
• You will play a pivotal role in engineering robust ETL/ELT workflows, real-time data processing streams, and scalable storage solutions using Databricks and Azure data technologies.
• The ideal candidate brings comprehensive expertise in PySpark, Python, SQL, Azure Data Factory, Delta Lake, and enterprise data modeling.
• Operating on-site in Abu Dhabi, you will collaborate closely with data scientists, business analysts, and analytics teams to support high-performance AI/ML workloads.
• Dicetek provides a dynamic, globally connected environment where your data engineering expertise directly drives enterprise intelligence and digital transformation.
• We welcome driven data professionals who excel in pipeline optimization, data quality enforcement, and MLOps automation.

• As a Data Engineer at Dicetek, your core responsibilities encompass end-to-end data pipeline development, data warehousing, and performance tuning.
• You will leverage Azure Data Factory, Databricks, and Delta Lake to build scalable ETL/ELT data ingestion and transformation workflows across distributed cloud environments.
• Utilizing Python and PySpark, you will process massive structured and unstructured datasets, implementing real-time data streaming solutions via Kafka.
• Your daily engineering duties involve designing dimensional data models, optimizing SQL queries, and ensuring high standards of data quality, security, and validation.
• You will collaborate proactively with Data Scientists to operationalize AI/ML models and support advanced analytics workloads through robust MLOps practices.
• Implementing continuous integration and continuous deployment (CI/CD) pipelines ensures automated, reliable data deployments across development and production stages.
• Troubleshooting pipeline bottlenecks, monitoring cloud resource utilization, and maintaining comprehensive technical documentation are essential to your success.

• Design, develop, test, and maintain scalable ETL and ELT data pipelines for enterprise data platforms.
• Build robust data integration and transformation solutions utilizing Azure Data Factory, Databricks, and Azure Data Lake.
• Develop advanced data models, data warehouses, and real-time data processing solutions using Kafka and PySpark.
• Implement comprehensive data quality, validation, security governance, and performance optimization practices.
• Support AI/ML and advanced analytics workloads by collaborating directly with Data Scientists and business stakeholders.
• Implement CI/CD and MLOps practices for automated, reliable, and version-controlled data deployments.
• Process, clean, and transform complex datasets using Python, SQL, and Delta Lake architectures.
• Monitor data pipeline execution metrics, troubleshoot ingestion errors, and execute rapid performance tuning.
• Ensure strict adherence to cloud data security standards, data privacy, and governance compliance.
• Maintain up-to-date technical documentation, data lineage diagrams, and pipeline runbooks.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Engineering, or a related technical field.
• Strong, proven professional experience designing and maintaining cloud-based data engineering solutions.
• Extensive hands-on expertise with Databricks, Azure Data Factory, Azure Data Lake, and Delta Lake.
• Deep proficiency in PySpark, Python, and advanced SQL programming for data transformation.
• Solid practical experience…