Data and AI Engineer
نظرة عامة على الوظيفة
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تاريخ الإعلاننوفمبر 15, 2025
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الموقع
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تاريخ إنتهاء الصلاحية--
المسمى الوظيفي
411_2641233
Overview
Job Title: Data & AI Engineer
Job Type: Full-Time
Location: Onsite – Sharjah, UAE
ملخص الوظيفة:
Join our team as a Data & AI Engineer and become an integral part of a forward-thinking organization in the education and research sector. You will architect robust and scalable data and AI solutions, driving innovation through advanced data engineering and end-to-end machine learning in a government setting. This role values written communication and thrives in an asynchronous, highly collaborative environment.
المسؤوليات
- Design, build, and optimize scalable ETL/ELT pipelines using Python, SQL, and orchestration tools such as Airflow, Talend, or Spark.
- Develop, deploy, and maintain machine learning models, implementing MLOps best practices for model versioning, monitoring, and retraining.
- Manage and scale cloud-based data and AI infrastructure, optimizing storage, compute resources, and performance for large-scale analytics.
- Ensure robust data governance and compliance, integrating regulatory requirements such as GDPR across data workflows and AI models.
- Integrate third-party APIs, automate complex data workflows, and support backend data structures for business intelligence and analysis.
- Collaborate cross-functionally to analyze trends, engineer features, and translate data insights for technical and non-technical audiences.
- Document pipelines, model architectures, and metadata while diagnosing and resolving technical issues with a root-cause approach.
Qualifications
- Advanced programming in Python, especially for data engineering and machine learning.
- Deep proficiency in SQL and hands-on experience with relational (MySQL, PostgreSQL) and non-relational (MongoDB) databases.
- Expertise with cloud-based data tools (Azure Data Factory, AWS) and ETL/ELT pipeline development.
- Proven ability with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and HuggingFace.
- Hands-on experience applying MLOps principles for model lifecycle management.
- Strong understanding of orchestration tools like Apache Airflow.
- Excellent written communication skills, vital for asynchronous collaboration.
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or related field.
- Minimum 7 years’ experience in data engineering, AI, or advanced analytics, with at least 2 years on AI/ML projects.
Preferred Qualifications
- Background in responsible AI, bias detection, and model explainability.
- Experience with data governance, compliance frameworks, and explainable AI (XAI).
- Exposure to advanced cloud-based AI orchestration and emerging ML technologies.
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2025-11-11 12:47:33