Ai Data Engineer (Ai Experience needed)

SALT; United Arab Emirates; On-site; USD 60,000 - 90,000; Full time

Job summary

A leading company in the UAE is hiring a Data Engineer with strong AI experience for a 1-year extendable contract. The role involves designing and optimizing data pipelines, implementing data governance frameworks, and supporting AI initiatives. Ideal candidates will have expertise in big data technologies and a passion for innovation in AI solutions.

Qualifications

• Experience with Data Governance frameworks and AI/ML support.
• Proficiency in SQL and scripting languages (Python, Scala).
• Hands-on experience with big data technologies (Hadoop, Spark).

Responsibilities

• Design and maintain scalable data pipelines for AI workloads.
• Implement data governance frameworks for security and compliance.
• Optimize data storage solutions for large volumes used in AI.

Skills

Data Governance

Data Pipeline Development

Data Integration

Data Storage

Performance Optimization

Monitoring and Maintenance

Documentation

Analytical Skills

Teamwork

Communication Skills

Education

Bachelor's degree in Computer Science or related field

Tools

Hadoop

Spark

Kafka

Flink

AWS

Azure

GCP

SQL

Python

Scala

Job description

***HIRING***

I am looking for a Data Engineer with strong AI experience to join my client in Dubai on a 1-year extendable contract. Please ONLY apply if you have the relevant skill sets; applications from software engineers, data analysts, etc., will not be considered.

You MUST have experience with Data Governance.

Data Governance: Implement data governance frameworks to ensure data security, privacy, integrity, and compliance with regulatory requirements, including data encryption, access controls, and auditing. This is crucial for responsible AI deployment.

Job Title: Data Engineer

Contract Length: 1 year extendable

Location: Onsite in Dubai

Start Date: TBC

Position Overview:

The client seeks a Data Engineer to join their AI specialist team in the UAE. As a Data Engineer, you will design, implement, and optimize data pipelines and infrastructure to support advanced AI systems. You will work closely with the team to ensure efficient collection, storage, processing, and analysis of large-scale data, enabling valuable insights and driving innovation across various domains.

Requirements:

1. Pipeline Development: Design, develop, and maintain scalable and reliable data pipelines to ingest, transform, and load diverse datasets, including structured, unstructured, streaming, and real-time data, with consideration for AI/ML workloads.
2. Data Integration: Implement robust processes to seamlessly integrate data from different sources, ensuring consistency, reliability, and quality for analytics and AI use cases.
3. Data Storage: Design and optimize storage solutions, including relational databases, NoSQL databases, data lakes, and cloud storage, for large data volumes used in AI and machine learning models.
4. Performance Optimization: Enhance data processing and query performance for scalability and efficiency, using techniques like indexing, partitioning, caching, and parallel processing, especially for AI model training and inference pipelines.
5. Data Governance: Implement frameworks to ensure data security, privacy, integrity, and regulatory compliance, including encryption, access controls, and auditing—crucial for responsible AI deployment.
6. Monitoring and Maintenance: Monitor data pipelines and infrastructure, proactively resolve issues, and perform routine maintenance to ensure system stability across AI and data science environments.
7. Documentation: Develop comprehensive documentation, including technical specifications, data flow diagrams, and operational procedures, to facilitate collaboration and knowledge sharing.
8. Technical Skills: Expertise in data modeling, ETL processes, data warehousing, proficiency in SQL and scripting languages (e.g., Python, Scala), especially for AI pipeline preparation and feature engineering.
9. Big Data Technologies: Hands-on experience with Hadoop, Spark, Kafka, Flink, and cloud platforms (AWS, Azure, GCP) used for AI workloads.
10. AI/ML Support: Experience supporting AI/ML initiatives, including dataset preparation, model data flows, MLOps integration, and experimentation tracking.
11. Skills: Excellent analytical, problem-solving, and communication skills, with the ability to translate complex concepts into clear insights.
12. Teamwork & Passion: Proven ability to work effectively in fast-paced, collaborative environments with a passion for innovation and continuous learning in AI solutions.