Senior Data Engineer

Location: Abu Dhabi, United Arab Emirates (UAE)
Employment Type: Full-Time, Permanent
Work Model: Onsite
Required Experience: 6–10 Years

We are seeking an experienced Senior Data Engineer to design, develop, and manage modern data platforms, scalable data pipelines, and cloud-based analytics solutions. The ideal candidate will have strong hands-on expertise in Microsoft Azure Data Services, large-scale data processing, data warehousing, ETL/ELT frameworks, and cloud-native data architectures.

The role involves building secure, reliable, and high-performance data solutions that support enterprise analytics, business intelligence, reporting, and AI/ML initiatives. The successful candidate will collaborate with cross-functional teams to deliver robust data engineering solutions aligned with business and technical requirements.

• Design, develop, and maintain scalable data platforms and data pipelines using Microsoft Azure services.
• Build and optimize batch and real-time data ingestion frameworks for structured, semi-structured, and unstructured data sources.
• Design and implement data lake, data warehouse, and lakehouse architectures to support analytics and reporting requirements.
• Develop, manage, and optimize ETL/ELT pipelines using modern cloud-native data engineering practices.
• Implement data transformation, cleansing, validation, and data quality frameworks to ensure data accuracy and consistency.
• Collaborate with business stakeholders, data analysts, data scientists, and application teams to translate requirements into scalable data solutions.
• Optimize data storage, processing, and query performance across enterprise data platforms.
• Implement data security, governance, monitoring, metadata management, and compliance best practices across Azure environments.
• Integrate enterprise data platforms with AI/ML solutions, business intelligence tools, and enterprise applications.
• Develop and maintain data models, reusable components, and efficient data processing workflows.
• Participate in architecture reviews, code reviews, technical troubleshooting, and continuous improvement initiatives.
• Support data platform reliability, scalability, high availability, and operational excellence.
• Implement version control, CI/CD pipelines, and DevOps practices for data engineering workloads.
• Contribute to technical documentation, knowledge sharing, and mentoring of team members where required.

• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related field.
• 6–10 years of professional experience in Data Engineering, Data Warehousing, or Enterprise Data Platform development.
• Strong hands-on experience with Microsoft Azure Data Services and cloud-based data engineering solutions.
• Practical expertise in Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake Storage Gen2 (ADLS Gen2), and Azure SQL Database.
• Experience designing, developing, and maintaining large-scale ETL/ELT pipelines and data integration frameworks.
• Strong proficiency in SQL, query optimization, and database performance tuning.
• Hands-on experience with PySpark, Apache Spark, and distributed data processing frameworks.
• Strong programming skills in Python, with exposure to Scala or Java being an advantage.
• Solid understanding of dimensional modeling, data warehousing principles, and modern lakehouse architectures.
• Experience processing structured, semi-structured, and unstructured data.
• Knowledge of data governance, data quality, metadata management, and data security best practices.
• Experience with REST APIs, enterprise data integration patterns, and connectivity with business applications.
• Familiarity with Git, CI/CD pipelines, and DevOps practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Effective communication and collaboration skills, with the ability to work across technical and business teams.

• Experience with Microsoft Fabric, OneLake, Dataflows, and Fabric Data Engineering workloads.
• Hands-on experience with Databricks, Delta Lake, and lakehouse implementations.
• Knowledge of real-time streaming technologies such as Azure Event Hubs, Apache Kafka, or Azure Stream Analytics.
• Experience supporting AI/ML and advanced analytics workloads through enterprise data platforms.
• Familiarity with Power BI datasets, semantic models, and enterprise reporting architectures.
• Experience with data governance tools such as Microsoft Purview.
• Microsoft Azure Data Engineering certifications are highly desirable.
• Experience working in Agile/Scrum environments.

• Experience with Microsoft Fabric Data Engineering and analytics solutions.
• Exposure to DataOps and MLOps practices.
• Knowledge of containerization technologies such as Docker and Kubernetes.
• Experience with Infrastructure as Code tools, including Terraform, ARM templates, or Bicep.
• Familiarity with Snowflake, Google BigQuery, or other cloud data warehouse platforms.
• Experience with enterprise-scale data migration, modernization, and cloud transformation projects.
• Understanding of Generative AI, vector databases, and data platforms supporting AI workloads.

• Location: Abu Dhabi, United Arab Emirates (UAE)
• Employment Type: Full-Time, Permanent
• Work Model: Onsite
• Required Experience: 6–10 Years

• Work on modern enterprise data platforms and cloud-based analytics solutions.
• Gain exposure to advanced Azure data engineering and lakehouse technologies.
• Contribute to data initiatives supporting business intelligence, analytics, and AI/ML applications.
• Collaborate with multidisciplinary teams in a technology-driven environment.
• Participate in enterprise data modernization and continuous improvement initiatives.