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 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.
Additional Skills: Nice to Have
- 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.
Work Location and Employment Details
- Location: Abu Dhabi, United Arab Emirates (UAE)
- Employment Type: Full-Time, Permanent
- Work Model: Onsite
- Required Experience: 6–10 Years
Why Join Us?
- 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.
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