Azure Data Engineer

Ghobash Group capitalizes on opportunities within promising industry sectors by either acquiring existing companies or establishing new businesses. Aligned with the needs of a growing portfolio, the Group established Aban Investment to administer a host of centralized business functions (finance, legal, HR, marketing, etc.) all aimed at delivering greater cost efficiencies, value and best practices to each of its business units.

Job Description

• Azure Data Platform Management: Design, implement, and manage Azure SQL databases, Azure Data Lake Storage, and related Azure & Fabric services.
• ETL Processes and Data Pipelines: Create, monitor, and optimize ETL (Extract, Transform, Load) workflows to integrate data from multiple sources into centralized systems, ensuring reliability and performance.
• SQL and Python Development: Utilize SQL for querying, analysing, and managing relational databases, and develop Python scripts to automate data processes, integrate data sources, and support advanced analytics.
• Big Data and Advanced Analytics: Leverage Azure Databricks for big data processing, analytics, and machine learning workflows, and utilize tools like Apache Spark and Hadoop for processing large datasets.
• Data Warehousing: Develop and maintain enterprise data warehouses to support analytics and reporting needs while ensuring seamless integration with visualization tools.
• Data Security and Compliance: Implement robust data security measures to protect sensitive data, maintain compliance with organizational and regulatory standards, and support disaster recovery processes.
• Collaboration and Documentation: Collaborate with cross-functional teams to gather requirements and deliver data solutions while maintaining detailed documentation of data architectures, ETL processes, and Power BI standards.
• AI Enablement: Design, implement and Manage data solutions for the AI needs.

IT Policies and IT Processes impacted/addressed by this position:

• Database Management Process: Adherence to data governance processes and policies to ensure data accuracy and security.
• Data Security Policy: Ensuring compliance with data protection and security guidelines.
• Change Management Policy: Following procedures for managing changes in technology and processes.
• Business Continuity Policy: Supporting business continuity planning and disaster recovery processes.
• IT Incident Management: Participating in the resolution of IT incidents related to data solutions.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Business Administration, or a related field.
• Advanced certifications in Azure Data Engineering, SQL, or Microsoft Power BI are preferred.

Additional Information

Experience:

• Minimum of 7 years of experience in data engineering, data warehousing, ETL processes, and business intelligence development.
• Proven expertise in Azure Data Factory, Azure Databricks, and Power BI development.
• Strong experience in SQL for database management, querying, and optimization.
• Any POC project for AI enablement for end users.
• Demonstrated proficiency in Python for data automation, analytics, and advanced transformations.
• Experience in managing data pipelines and integrating large data sets for analysis.
• Demonstrated experience in collaborating with stakeholders and presenting data-driven insights.
• Experience in building Data solutions for AI recipients that successfully helped the business with a tangible benefit.

Skills & Abilities:

• Proficient in Azure services: Data Factory, Databricks, Data Lake, SQL Database, and Synapse Analytics.
• Advanced Power BI expertise, including DAX, data modelling, and report development.
• Strong SQL and Python skills for data processing, analysis, and automation.
• Experience with big data frameworks like Apache Spark and Hadoop.
• Proficiency in relational databases: Microsoft SQL Server, MySQL, and PostgreSQL.
• Excellent organizational, problem-solving, and communication skills.
• Familiarity with data security and compliance standards.