Data and AI Specialist

• Design, build, and manage data pipelines and analytics platforms using Azure Data Factory, Synapse Analytics, and Data Lake. • Develop, train, and deploy machine learning and AI models on Azure Machine Learning and integrate with other cloud platforms where needed. • Implement data governance, security, and compliance controls across multi-cloud environments. • Contribute to and support the organization’s AI and data strategy, ensuring alignment with digital transformation initiatives. • Ensure multi-cloud interoperability, including the ability to migrate and optimize AI workloads across Azure, Google Cloud, and AWS. • Conduct data analysis, reporting, and visualization using Power BI, Tableau, or equivalent tools. • Evaluate and adopt emerging AI/ML services from multiple cloud providers to maximize value. • Document and enforce AI governance frameworks, policies, and ethical guidelines. • Collaborate with IT, governance bodies, and business stakeholders to identify AI use cases that deliver tangible business outcomes. • Provide technical mentorship, training, and awareness sessions on AI and data tools to internal teams. • Master’s degree in AI, Business Analytics, or Information Systems • Azure certifications (Azure AI Engineer Associate, Azure Data Scientist, or Azure Solutions Architect) • Multi-cloud or vendor certifications (e.g. Google Cloud Professional ML Engineer) • Strong hands-on experience with Microsoft Azure AI and Data Services (Azure ML, Synapse, Cognitive Services, Data Factory, Data Lake) • Familiarity with multi-cloud integration and migration strategies • Proficiency in Python, R, SQL, and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn) • Knowledge of data governance, MLOps, and ethical AI frameworks • Experience in data visualization with Power BI, Tableau, or equivalent • Fluency in English; proficiency in Arabic is highly desirable • Strategic mindset with the ability to bridge AI innovation and business needs • Strong communication skills to engage both technical and non-technical audiences • Agile, adaptable, and experienced in multi-cloud and hybrid environments • High integrity in managing data, privacy, and ethical considerations • Collaborative and proactive in cross-functional teams