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 Dev Ops 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 Dev Ops practices.
• Strong…