Data and AI Manager-Arabic Speaker

Overview

Overview

• We are seeking a Senior Data & AI Consultant with 5+ years of experience spanning data architecture, data governance, and AI/ML solution development.
• The ideal candidate should have
• broad exposure across the Data & AI lifecycle
• from data strategy and governance to architecture, engineering, and advanced analytics
• while
• specializing in at least one of the following areas
• : (1) Data Strategy & Governance, or (2) Data Management, or (3) Data Science/AI/ML Engineering.
• Candidate should be bilingual with full proficiency in Arabic and English.
• This role requires strong technical depth, consulting acumen, and client-facing communication skills.
• The consultant will work with diverse clients across industries, driving enterprise data and AI transformation programs.

1. Data Strategy & Advisory

• Develop and implement enterprise-wide data and AI strategies aligned with business goals.
• Assess organizational data & AI maturity and define transformation roadmaps.
• Advise clients on data lifecycle management, and responsible AI adoption.
• Conduct workshops with CXOs and business leaders to align business priorities with data & AI initiatives.

2. Data Architecture & Engineering

• Design and implement modern data platforms on Microsoft Azure, ensuring scalability, performance, and compliance.
• Develop conceptual, logical, and physical data models for operational and analytical use cases.
• Architect data pipelines for batch and real-time ingestion using Azure Data Factory, Synapse, Databricks, and related tools.
• Implement data quality, metadata management, and lineage tracking leveraging Azure Purview or equivalent governance tools.
• Collaborate with AI teams to enable data readiness for AI/ML workloads and ensure seamless integration across the ecosystem.

3. AI & Advanced Analytics

• Lead AI/ML solution design and deployment, translating business problems into technical AI solutions.
• Build and operationalize machine learning and Generative AI use cases on Azure (e.g., Azure Machine Learning, OpenAI, Cognitive Services).
• Implement MLOps practices for CI/CD, model monitoring, and lifecycle management.
• Ensure Responsible AI practices are embedded - fairness, explainability, transparency, and ethical governance.
• Collaborate with data teams to develop end-to-end AI pipelines, from data sourcing to model deployment.

4. Consulting, Pre-Sales & Thought Leadership

• Lead client workshops, PoCs, and pre-sales solutioning across Data and AI engagements.
• Support proposal development, client demos, and design of value-driven use cases.
• Contribute to thought leadership through whitepapers, blogs, and conference presentations.
• Mentor junior consultants and foster a culture of learning and innovation.

Education & Experience

• Bachelor’s or Master’s in Computer Science, Data Engineering, AI, or Information Systems.
• 5+ years of experience in data & AI consulting, architecture, or strategy roles.
• Experience working with Azure ecosystem and familiarity with one or more of: AWS, GCP.
• Experience across multiple industries such as Public Sector, Financial Services, Oil & Gas, Government, Healthcare, and Utilities.
• Technical Expertise (Candidates should have expertise in one or more domains)
• ***A.
• Data Management***
• Azure Data Factory, Synapse Analytics, Data Lake, Delta Lake, Databricks, Event Hubs, Stream Analytics.
• Proficiency in SQL, Python, and Spark.
• Data Modeling (Conceptual, Logical, Physical), ETL/ELT, Data Quality frameworks.
• Familiarity with MS Fabric and open-source technologies (Airflow, Kafka, Presto).

*B. Data Governance & Strategy*

• Knowledge of DAMA-DMBOK, CMMI-DMM, or equivalent maturity models.
• Experience with Informatica Data Governance Suite of Solutions (Axon, IDQ, EDC, IDMC).
• Understanding of global data privacy and sovereignty laws.
• Ability to define data governance operating models and stewardship structures.
• ***C.
• AI/ML Engineering***
• Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, or Azure ML.
• Hands-on experience with Generative AI (LLMs, RAG, Prompt Engineering).
• Strong understanding of MLOps pipelines and model lifecycle automation.
• Experience in at least three AI domains: NLP, Predictive Modeling, Computer Vision, Recommender Systems, or Anomaly Detection.

Consulting & Leadership Skills

Certifications (Preferred)