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What is Strategy Department?
The Strategy Department is responsible for the VRP plan and generating the strategy going forward and setting the direction and identifying the areas of focus for the implementation and delivery of DARP initiatives. Working jointly with sector counterparts to plan for delivery, monitor progress and solve implementation challenges, This Department has three sections (Strategy & Performance Management, Analytics & Innovation, and Excellence & Control).
What is the Analytics and Innovation Department?
The Analytics and Innovation Department is the Department that Develop a one-stop-shop digital super hub aiming to transform the entire sector of Hajj and Umrah for the purpose of improving the customer experience, enabling better governance, supporting in bridging gaps in capacities, and enabling new and better business models for investors.
What you’ll do?
- Build data pipelines: Managed data pipelines consist of a series of stages through which data flows (for example, from data sources or endpoints of acquisition to integration to consumption for specific use cases). These data pipelines have to be created, maintained, and optimized as workloads move from development to production for specific use cases. Architecting, creating, and maintaining data pipelines will be the primary responsibility of the data engineer.
- Drive Automation through effective metadata management: The data engineer will be responsible for using innovative and modern tools, techniques and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity. The data engineer will also need to assist with renovating the data management infrastructure to drive automation in data integration and management.
- Collaborate across departments: The data engineer will need strong collaboration skills in order to work with varied stakeholders within the organization. In particular, the data engineer will work in close relationship with data science teams and with business (data) analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
- Participate in ensuring compliance and governance during data use: It will be the responsibility of the data engineer to ensure that the data users and consumers use the data provisioned to them responsibly through data governance and compliance initiatives. Data engineers should work with data governance teams (and information stewards within these teams) and participate in vetting and promoting content created in the business and by data scientists to the curated data catalog for governed reuse.
Who you are?
We always strive to create a creative environment that supports creativity and contributes to its growth by attracting the best talent with the following minimum requirements:
Your Education and Experience:
- Bachelor’s degree in Business Administration, Engineering, Information Science, Computer Science, or any related field.
- 3+ years’ of work experience in data management disciplines including (data integration, modeling, optimization, and data quality) and/or other areas directly relevant to data engineering responsibilities and tasks.
- Strong ability to design, build, and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
- The ability to work with both IT and business in integrating analytics and data science output into business processes and workflows.
- Strong experience with popular database programming languages including [SQL, PL/SQL, others] for relational databases.
- Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include [ETL/ELT, data replication/CDC, message-oriented data movement, API design and access] and upcoming data ingestion and integration technologies such as [stream data integration, CEP and data virtualization].
- Strong experience in working with SQL on Microsoft SQL Server.
- Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production.
- Basic experience working with Power BI for semantic-layer-based data discovery.
- Strong experience of using Alteryx as ETL tool.