Manager - Data Engineering

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Majid Al Futtaim Holding is the leading shopping mall, retail, communities, entertainment developer and operator in the Middle East, North Africa, and Central Asia regions. With over 43,000 people, revenues of over US $ 11 Billion, and operations in 18 countries. Some of the iconic brands we carry include Mall of the Emirates, Carrefour, All Saints, Lego, City Center, Abercrombie & Fitch, & Vox Cinemas.

We believe in making Great Moments for Everyone, Every day.

The Manager - Data Engineering is responsible for steering and building the Next Gen Business Intelligence & Data Strategy, Data Virtualization, and Data Lakes Warehousing, through researching and experimenting with emerging data technologies and industry trends with a view to bringing business value through early adoption. The role holder is also responsible for developing and defining key business questions, support analysis, improvement and creation of key metrics and dashboards for the learning organization to provide effective solutions to be shared with internal customers at all levels of the organization, supporting in drafting strategic documents for the senior stakeholders.

He/she will be responsible for the technical implementation of high-quality, enterprise-grade solutions and be in one of the largest and most complex data warehouse environments, which requires deep expertise in the design, creation, management, and business use of large datasets, as well as designing, implementing, and operating stable, scalable, low-cost solutions to flow data from production systems into the data warehouse and into end-user facing applications (Power BI).

The Data Engineer’s technical skills and creativity will prove instrumental in creating custom data pipeline solutions, where existing tools prove insufficient.

• Data Engineering for Business Intelligence & Data Analysis & Reporting
• Transform and improve performance of existing reporting & analytics use cases with more efficient and state of the art data engineering solutions
• Contribute to business analysis of the OLTP and OLAP data and in decision support with extensive database programming
• Understand business requirements in BI context and design data models to transform raw data into meaningful insights
• Data Warehouse Architecture & Tools
• Build and maintain a scalable data lineage system to improve data infrastructure reliability and efficiency
• Build the infrastructure required for optimal ETL of data from a wide variety of data sources using SQL and ‘big data’ technologies
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc
• Identify opportunities for data acquisition and build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
• Ensure the architecture will support all the business needs to drive actionable insights
• Own end-to-end ETL process to build data pipelines, from planning to collection to analysis, including writing custom queries, data cleaning and manipulation, and the ability to work with large datasets
• Acquire data from primary or secondary data sources and maintain databases / data systems and in charge of ensuring consistent data quality on a continuous basis
• Create and maintain optimal data pipeline architecture, assemble large, complex data sets that meet functional / non-functional business requirements
• Design, develop, test, and deploy scalable Power BI dashboards and develop real-time database solutions and pipeline to Power BI Dashboard
• Design ETL using SSIS Packages to reprocess any date data at any time using Reprocess Logic

• Write T-SQL Stored procedures for performing automation tasks, Performed and fine-tuned Stored Procedures and SQL Queries and User Defined Functions, and for Triggers, Constraints, and Indexes using various DDL and DML commands
• Maintain the Log and Audit information in SQL…