Data Engineer

JOB PURPOSE:

The Data Engineer is responsible for designing, developing, and maintaining reliable data pipelines, integrations, and analytical platforms that support business decision-making. The role involves collaborating with stakeholders to translate business requirements into data solutions, optimizing performance, and ensuring data quality, accessibility, and security across all systems.

RESPONSIBILITIES/DUTIES

Data Engineering & Integration

• Design, build, and maintain scalable ETL/ELT processes from multiple source systems to the data warehouse and MIS databases.
• Develop and automate data workflows to ensure efficiency, reliability, and reusability.
• Maintain high-quality data architecture that supports reporting, analytics, and machine learning applications.
• Perform data validation, cleansing, and enrichment to ensure accuracy and consistency.
• Troubleshoot and resolve data integration or pipeline issues promptly.

Business Intelligence & Reporting

• Collaborate with business stakeholders to identify reporting needs and define KPIs.
• Develop and maintain interactive dashboards and analytical reports using BI tools (e.g., Power BI, QlikSense).
• Translate complex datasets into clear, actionable insights through data visualization.
• Continuously improve BI performance and usability for business users.

System Administration & Support

• Manage the deployment, configuration, and performance of BI and data applications.
• Provide technical support during User Acceptance Testing (UAT) and production phases.
• Coordinate with vendors and internal IT teams to resolve incidents and implement updates.
• Monitor application health, document system changes, and maintain operational logs.

Governance, Documentation & Continuous Improvement

• Maintain comprehensive documentation of data models, processes, and integrations.
• Contribute to data governance efforts, ensuring compliance with data management standards.
• Recommend and implement process improvements to enhance scalability and data utilization.
• Stay updated on emerging technologies in data engineering and analytics.

Safety Responsibilities

• Promote a positive safety culture within the workplace and attend any safety-related meetings or briefings as required within the job role.
• Comply with the requirements of RDMC RQHSE Policy and Safety Management System.
• Be mindful that Safety, Security, and Environmental protection are everyone’s responsibility.
• All staff members are accountable for reporting and intervening in any Safety, Security, or Environmental violations.

ESSENTIAL QUALIFICATIONS, KNOWLEDGE & EXPERIENCE

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Certifications in Data Engineering, BI Tools, or Data Management (e.g., Microsoft, Google Cloud, AWS) are an advantage.
• Fluency in English and Arabic; French is a plus.

Knowledge

• Strong understanding of data engineering concepts, data modeling, and integration frameworks.
• Proficiency in SQL and relational database engines (SQL Server, MySQL, etc.).
• Experience with BI tools such as Power BI or QlikSense for dashboard development.
• Good command of Python or equivalent scripting languages for data transformation.
• Familiarity with data science fundamentals and visualization best practices.
• Understanding of data governance and data quality management principles.

Experience

• 3-5 years of experience in data engineering, BI development, or ETL-focused roles.
• Demonstrated experience in building and maintaining scalable data pipelines and dashboards.
• Proven ability to collaborate cross-functionally to deliver high-impact analytics solutions.

DESIRED BEHAVIORS & EXPERIENCES

• Analytical Mindset: Naturally curious and data-driven, with the ability to identify trends and insights.
• Communication & Collaboration: Strong interpersonal and presentation skills, able to translate complex data into clear business narratives.
• Ownership & Initiative: Proactive, self-motivated, and accountable for project outcomes.
• Organization & Detail Orientation: Strong time management and prioritization abilities.
• Adaptability: Comfortable working in fast-paced, evolving environments.
• Customer Focus: Committed to delivering value and providing excellent internal stakeholder support.
• Innovation: Eager to explore new methods and tools to improve data processes and decision-making.