Location: Abu Dhabi, United Arab Emirates (UAE)
Employment Type: Full-Time, Permanent
Work Model: Onsite
Required Experience: 6–10 Years
Job Summary
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.
Key Responsibilities
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.
Required Skills and Qualifications
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.
Preferred Qualifications
Experience with…