Manager / Senior Manager – Data & AI Consulting

Overview

Annual Compensation

Mandatory Skills

Required Qualifications

• Candidate must be bilingual (Arabic & English).
• At least 5+ years' experience in Data/AI consulting, architecture, or strategy roles.
• Strong experience in the Azure ecosystem (Azure Data Factory, Synapse, Purview, Databricks).
• Exposure to industries like Public Sector, BFSI, Oil & Gas, Government, Healthcare, Utilities.

About The Role

• Data Strategy & Advisory-

• Develop enterprise-wide Data & AI strategies and transformation roadmaps.
• Assess data maturity and recommend improvements.
• Conduct CXO-level workshops to align business goals with Data & AI initiatives.
• Guide clients on responsible AI practices.

• Data Architecture & Engineering

• Design scalable data platforms on Microsoft Azure.
• Develop data models and architect batch/real-time pipelines using ADF, Synapse, Databricks, etc.
• Implement data quality, metadata, and lineage solutions (Azure Purview).
• Partner with AI teams to ensure data readiness for ML/AI use cases.

• AI & Advanced Analytics

• Lead end-to-end AI/ML solution development on Azure ML, OpenAI, Cognitive Services.
• Build ML & Generative AI use cases and implement MLOps (CI/CD, monitoring).
• Ensure Responsible AI (fairness, explainability, governance).
• Collaborate on full AI pipeline—from data sourcing to deployment.

• Consulting, Pre-Sales & Leadership

• Lead client workshops, PoCs, demos, and pre-sales engagements.
• Support proposal writing and solution design.
• Contribute to thought leadership (blogs, whitepapers, events).
• Mentor junior consultants and support delivery excellence.

Technical Expertise (Any One Or More Areas)

• Data Management:
• Azure Data Factory, Synapse, Data Lake, Databricks, Event Hubs.
• Strong SQL, Python, Spark.
• Data modeling, ETL/ELT, data quality frameworks.
• Knowledge of MS Fabric or open-source tools (Airflow, Kafka).

• Data Governance & Strategy

• Familiarity with DAMA-DMBOK, CMMI-DMM.
• Experience with Informatica (Axon, IDQ, EDC, IDMC).
• Understanding of data privacy, governance operating models, stewardship.
• AI/ML Engineering:
• Python, TensorFlow, PyTorch, Scikit-learn, Azure ML.
• Experience with Generative AI (LLMs, RAG, prompt engineering).
• Knowledge in at least 3 areas: NLP, Predictive Modeling, Computer Vision, Recommender Systems, Anomaly Detection.
• Practical experience in MLOps.