Data Engineer – Analytics & AI

American University; United Arab Emirates; On-site; AED 120,000 - 200,000; Full time

Job summary

A leading educational institution in the United Arab Emirates is seeking a highly skilled Data Engineer to enhance institutional research and data analytics. This role involves designing data pipelines, developing visualizations, and implementing AI models to support decision-making processes. The ideal candidate will possess strong skills in SQL and Python, and a relevant degree along with 3-5 years of experience in data engineering, preferably within higher education. Competitive salary and growth opportunities available.

Benefits

Competitive salary

Professional growth opportunities

Qualifications

• 3–5 years of experience in data engineering, analytics, or business intelligence.
• Hands-on experience with AI/ML libraries like scikit-learn, TensorFlow, or PyTorch.
• Proven track record of building data models, pipelines, and visualization dashboards.

Responsibilities

• Design, develop, and maintain data pipelines for ingestion and integration.
• Create dashboards and KPIs using Power BI and other tools.
• Develop predictive models and algorithms for various insights.

Skills

Data engineering and pipeline design

SQL

Python

Cloud data platforms

Machine learning techniques

Data visualization and BI tools

Data governance

Problem-solving skills

Communication skills

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Information Systems, Statistics, or related field

Tools

Power BI

Tableau

Docker

Kubernetes

Prometheus

Grafana

Job description

The American University in the Emirates is seeking a highly skilled and motivated Data Engineerto join our Institutional Effectiveness and Data Analytics team. The successful candidate will design and implementdata pipelinesto support strategic decision-making, institutional research, accreditation, and academic/administrative operations. The role involves buildingdata ingestion frameworksfrom multiple sources, preparing datasets forAI, predictive analysis, clustering, and classification models, and developingvisualizations, KPIs, and scorecards for executive reporting.

Key Responsibilities

• Design, develop, and maintaindata pipelinesfor ingestion, transformation, and integration from diverse sources (databases, APIs, cloud systems, ERP, LMS, CRM, etc.).
• Build and optimizeETL/ELT workflowsto ensure data accuracy, consistency, and availability.
• Createdashboards, KPIs, and scorecardsusingPower BI and other visualization toolsto support academic, administrative, and executive stakeholders.
• Developpredictive models, clustering, and classification algorithmsfor student success, enrollment forecasting, and operational insights.
• Experience deploying ML models in production using Docker, Kubernetes, and serverless frameworks.
• Familiar with monitoring tools such as Prometheus, Grafana, and Langfuse for real-time tracking, alerting, and performance diagnostics.
• Collaborate with academic and administrative departments to identify analytical needs and transform them into scalable data solutions.
• Ensuredata governance, security, and compliancewith university and regulatory policies.
• SupportAI-driven initiativesin institutional research, student engagement, and accreditation compliance.
• Continuously evaluate emerging tools and methodologies fordata engineering, visualization, and analytics.

Required Skills & Competencies

• Strong proficiency indata engineering and pipeline design(ETL/ELT).
• Expertise inSQL, Pythonfor data processing and analytics.
• Experience withcloud data platforms(Azure Data Factory, AWS Glue, or GCP BigQuery) preferred.
• Solid understanding ofmachine learning techniques: regression, classification, clustering, and predictive analysis.
• Advanced skills indata visualization and BI tools: Power BI, Tableau.
• Ability to design and developKPI dashboards, scorecards, and executive reports.
• Familiarity withdata governance, quality, and metadata management.
• Strong problem-solving skills with the ability to translate business questions into analytical models.
• Excellent communication and collaboration skills to work with academic and administrative stakeholders.

Qualifications

• Bachelor’s or Master’s degree inData Science, Computer Science, Information Systems, Statistics, or related field.
• 3–5 years of experiencein data engineering, analytics, or business intelligence (experience in higher education preferred).
• Hands-on experience withAI/ML libraries(scikit-learn, TensorFlow, PyTorch, etc.) is an advantage.
• Proven track record of buildingdata models, pipelines, and visualization dashboards.
• Certification inAzure Data Engineer, AWS Data Analytics, or Tableau/Power BIis a plus.

Preferred Attributes

• Experience working in anacademic/university settingwith exposure tostudent information systems and accreditation reporting.
• Knowledge ofinstitutional research methodologiesand KPI frameworks.
• Strong passion forleveraging data for student success and organizational excellence.