Data Analyst (School Performance Monitoring Section)

Department Definition

Main Job Duties & Responsibilities

• Collect, validate, and consolidate school performance data, including academic results, attendance, staffing indicators, and operational KPIs.
• Develop and maintain performance dashboards to monitor trends across schools and clusters.
• Analyze student achievement data and identify performance gaps at school, cycle, and subject levels.
• Track key indicators such as attendance, retention, staffing ratios, and compliance metrics.
• Conduct comparative analysis and benchmarking across schools to support targeted interventions.
• Identify performance risks and flag early warning indicators to support proactive decision-making.
• Prepare periodic analytical reports and executive summaries for leadership.
• Support mid-year and annual performance review cycles with structured data insights.
• Ensure consistency, integrity, and alignment of data across multiple reporting systems.
• Collaborate with relevant sectors (curriculum, HR, digital, assessment) to align datasets and performance measures.
• Support evidence-based policy recommendations and improvement initiatives.
• Contribute to the continuous enhancement of KPIs, monitoring frameworks, and reporting tools.

Skills, Qualifications & Experience

• Bachelor s degree in Data Analytics, Statistics, Business Analytics, Economics, Education, Information Systems, or a related field.
• Professional certifications in data analysis or business intelligence tools are an advantage.
• Minimum of 3 5 years experience in data analysis or performance monitoring, preferably within education or government sectors.
• Experience working with academic performance data, KPIs, and large datasets.
• Practical experience in dashboard design and automated reporting.
• Advanced proficiency in Excel and data visualization tools such as Power BI.
• Strong analytical and statistical skills with the ability to interpret educational performance data.
• Knowledge of database tools and data validation techniques.
• Ability to translate complex analysis into clear insights for decision-makers.
• High attention to detail and strong organizational skills.
• Strong communication and presentation skills.