Data and AI Engineer

micro1; Sharjah; On-site; AED 200,000 - 300,000; Full time

Job summary

An innovative technology firm in Sharjah is seeking a Data & AI Engineer to develop robust data solutions. This role involves creating scalable systems using advanced data engineering and machine learning models, ensuring data governance and compliance. Ideal candidates will have significant experience in Python, SQL, and cloud tools. Strong communication skills are essential for this collaborative position.

Qualifications

• Minimum 7 years' experience in data engineering, AI, or advanced analytics.
• At least 2 years on AI/ML projects.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines.
• Develop, deploy, and maintain machine learning models.
• Manage and scale cloud-based data and AI infrastructure.
• Ensure robust data governance and compliance.
• Integrate third-party APIs and automate complex data workflows.
• Collaborate cross-functionally to analyze trends and engineer features.
• Document pipelines and model architectures while diagnosing technical issues.

Skills

Advanced programming in Python

Deep proficiency in SQL

Expertise with cloud-based data tools

Proven ability with AI/ML frameworks

Hands-on experience applying MLOps principles

Strong understanding of orchestration tools

Excellent written communication skills

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

Azure Data Factory

AWS

TensorFlow

PyTorch

Scikit-learn

HuggingFace

Apache Airflow

MySQL

PostgreSQL

MongoDB

Job description

Overview

Job Title: Data & AI Engineer

Job Type: Full-Time

Location: Onsite - Sharjah, UAE

Job Summary:

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.

Responsibilities

• 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.