Data Engineer

As a Data Engineer at NEOM EC-12, you will play a pivotal role in shaping and implementing our data strategy. This strategic position is crucial for transforming raw data into meaningful insights, contributing to informed decision-making across various stakeholders. If you are passionate about leveraging data to drive positive educational outcomes, this role offers a unique opportunity to lead the development of a robust data infrastructure.

KEY ACCOUNTABILITIES & ACTIVITIES

Data Strategy Development:

• Collaborate with stakeholders to assess existing data infrastructure and contribute to the development of a comprehensive data strategy aligned with organizational objectives.
• Create a roadmap for implementing the data strategy, outlining key milestones and timelines for achieving strategic goals.
• Explore emerging technologies and trends in data engineering to propose innovative solutions that enhance the organization's data capabilities.
• Anticipate future data needs and design scalable data solutions to adapt to evolving organizational requirements.
• Ensure alignment of the data strategy with broader business goals and objectives.

Dashboard Creation:

• Work closely with stakeholders to understand reporting and visualization requirements.
• Design and implement data models supporting the creation of interactive and insightful dashboards.
• Utilize visualization tools like Tableau, Power BI, or equivalent for creating visually appealing and user-friendly dashboards.
• Optimize queries and data retrieval processes to ensure real-time or near-real-time insights.
• Provide training and documentation to end-users on effective usage and interpretation of dashboard information.

Data Integration and Management:

• Design, implement, and maintain Extract, Transform, Load (ETL) processes for efficient data integration from various sources.
• Implement data quality processes to ensure accuracy and reliability of integrated data.
• Develop strategies for managing master data to ensure consistency across the organization.
• Implement solutions for real-time data processing and streaming as required by the business.
• Conduct rigorous testing of integrated data to identify and resolve any issues related to data integrity.

Database Architecture:

• Design and implement database structures aligned with performance, scalability, and business requirements.
• Implement effective indexing strategies to optimize database query performance.
• Apply normalization and denormalization techniques based on the specific needs of the data.
• Develop and implement robust backup and recovery plans to safeguard data against loss or corruption.
• Implement security measures to protect sensitive data, including access controls, encryption, and auditing.

Collaboration with stakeholders:

• Collaborate with stakeholders to understand their data requirements for analytical purposes.
• Assist stakeholders in exploring and understanding available data sources, ensuring access to relevant information.
• Work closely with stakeholders to optimize SQL queries and provide guidance on efficient data retrieval techniques.
• Collaborate in interpreting data results, providing insights, and helping stakeholders derive meaningful conclusions.
• Establish a continuous feedback loop with stakeholders to refine and enhance data solutions based on evolving needs.

Data Governance and Quality:

• Contribute to the development and enforcement of data governance policies and standards.
• Establish processes and tools for ongoing monitoring of data quality, initiating corrective actions when necessary.
• Ensure data practices adhere to regulatory requirements and industry standards related to data governance.
• Conduct training sessions and communicate data governance principles to stakeholders to foster a culture of data quality and compliance.

Cloud-Based Solutions:

• Design and implement data solutions leveraging cloud platforms such as AWS, Azure, or Google Cloud.
• Utilize cloud scalability features to accommodate growing data volumes and processing demands.
• Implement cost-effective solutions in the cloud by optimizing resource utilization and leveraging serverless or managed services.
• Implement robust security measures in the cloud, including encryption, access controls, and monitoring.

Training and Documentation:

• Provide training to end-users on data tools, dashboards, and reporting systems.
• Create and maintain comprehensive documentation for data engineering processes.

Security and Compliance:

• Implement robust security measures to protect sensitive data.
• Ensure compliance with data privacy regulations and standards.