Data & AI Engineer - Contract

Job Title:
Data & AI Engineer

Client Industry:
Education and Research (Government Sector)

Work Location:
Onsite - Sharjah, UAE

Working Days:
Monday to Friday

Working Hours:
8:00 AM - 5:00 PM

Contract Duration:
12 months (renewable to long-term)

Notice Period:
30 days or less

Benefits:
As per UAE labor law for self, plus an Annual Air Ticket allowance of AED 1500.

About the Role:

We are seeking a highly skilled and experienced Data & AI Engineer to join a dynamic team within the education and research sector. You will be responsible for designing, building, and maintaining robust, scalable data and AI solutions. This role requires advanced technical expertise across the entire data lifecycle, from building automated data pipelines to developing, deploying, and managing machine learning models in a production environment.

Key Responsibilities:

• Data Pipeline Engineering:
  Design, develop, maintain, and optimize scalable, automated ETL/ELT pipelines using Python, SQL, and orchestration tools (e.g., Airflow, Talend, Spark).
• AI/ML Model Development & MLOps:
  Apply advanced expertise in AI algorithms (supervised, unsupervised, reinforcement learning) to build, version, deploy, monitor, and retrain machine learning models. Manage the full MLOps lifecycle.
• Cloud & Data Infrastructure:
  Manage and optimize cloud environments for data pipelines and AI models, including resource scaling, storage solutions, and cost/performance tuning. Design and maintain large-scale data lakes and warehouses.
• Data Governance & Compliance:
  Implement data governance frameworks, ensure data lineage, and integrate regulatory compliance checks (e.g., GDPR) into pipelines and AI models.
• API Integration & Automation:
  Integrate third-party APIs into data workflows, automate complex data processes using Python scripting and scheduling tools, and support backend data structures for BI dashboards.
• Analysis & Collaboration:
  Conduct predictive and trend analysis, perform feature engineering, and collaborate with cross-functional teams to translate data findings for non-technical audiences.
• Documentation & Troubleshooting:
  Document data workflows, model architectures, and metadata. Diagnose and resolve data pipeline and AI model failures with root-cause analysis.

Skills and Competencies Required:

• Must-Have Technical Skills:
• Advanced programming expertise in
  Python
  for data engineering and ML.
• Advanced proficiency in
  SQL
  and experience with relational (MySQL, PostgreSQL) and non-relational (MongoDB) databases.
• Hands-on experience with cloud data tools (e.g.,
  Azure Data Factory
  , AWS) and building data pipelines.
• Working knowledge of
  AI/ML frameworks
  (e.g., TensorFlow, PyTorch, Scikit-learn, HuggingFace).
• Proven experience with
  MLOps
  practices, including model versioning and lifecycle management.
• Experience with orchestration tools like
  Apache Airflow
  .
• Desirable Knowledge:
• Responsible AI practices (bias detection, model explainability).
• Descriptive and inferential statistical techniques.
• Data governance and regulatory compliance.
• Soft Skills:
• Strong interpersonal and collaboration skills.
• Advanced troubleshooting and problem-solving abilities.
• Capacity to handle multiple projects in a dynamic environment.
• Proactive learner in emerging AI/ML technologies.

Educational Qualification:

• Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence, or Machine Learning.

Professional Experience:

• A minimum of
  7 years
  of cumulative experience in data engineering, AI, or advanced analytics roles.
• At least
  2 years
  of dedicated, hands-on experience in AI/ML project delivery, model development, or deployment.
• Proficiency in data pipeline development, ETL/ELT processes, cloud data services (Azure, AWS), and machine learning frameworks.
• Preferred:
  Exposure to AI governance, explainable AI (XAI), and cloud-based AI service orchestration.