Senior Data Engineer - AI & Data Infrastructure

**Please note that the job is on-site in Dubai, relocation is a must (company sponsor)**

Responsibilities:

• The Data Engineer for the AI and Data Team will play a crucial role in designing, building, and maintaining scalable data infrastructure and pipelines.
• This position involves working closely with data scientists, AI engineers, and software developers to ensure efficient data flow and accessibility for our AI and data initiatives.

Infrastructure Management:

• Design, develop, and maintain robust and scalable data pipelines to handle large datasets using both on-premise and cloud platforms (e.g., AWS, GCP, Azure).
• Implement and manage data storage solutions, including databases and data lakes, ensuring data integrity and performance.

Data Integration:

• Integrate data from various internal and external sources such as databases, APIs, flat files, and streaming data.
• Ensure data consistency, quality, and reliability through rigorous validation and transformation processes.

ETL Development:

• Develop and implement ETL (Extract, Transform, Load) processes to automate data ingestion, transformation, and loading into data warehouses and lakes.
• Optimize ETL workflows to ensure efficient processing and minimize data latency.

Data Quality & Governance:

• Implement data quality checks and validation processes to ensure data accuracy and completeness.
• Develop data governance frameworks and policies to manage data lifecycle, metadata, and lineage.

Collaboration and Support:

• Work closely with data scientists, AI engineers, and developers to understand their data needs and provide technical support.
• Facilitate effective communication and collaboration between the AI and data teams and other technical teams.

Continuous Improvement:

• Identify areas for improvement in data infrastructure and pipeline processes.
• Stay updated with the latest industry trends and technologies related to data engineering and big data.

Requirements:

Education:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field. A Master’s degree is a plus.

Experience:

• Minimum of 3-5 years of experience in data engineering or a similar role.
• Proven experience with on-premise and cloud platforms (AWS, GCP, Azure).
• Strong background in data integration, ETL processes, and data pipeline development.
• Led the design and development of high-performance AI and data platforms, including IDEs, permission management, data pipelines, code management and model deployment systems.

Skills:

• Proficiency in scripting and programming languages (e.g., Python, SQL, Bash).
• Strong knowledge of data storage solutions and databases (e.g., SQL, NoSQL, data lakes).
• Experience with big data technologies (e.g., Apache Spark, Hadoop).
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI).
• Understanding of data engineering and MLOps methodologies.
• Awareness of security best practices in data environments.
• Excellent problem-solving skills and attention to detail.

Preferred Qualifications:

• Managed on-premise Spark cluster for hands-on big data processing - focuses on both deployment and usage.

What we offer:

• Competitive Compensation: Enjoy a salary package tailored to your skills and experience, along with performance-based bonuses.
• Comprehensive Benefits: We support your well-being with accommodation, meal allowances, and assistance with work visa processing.
• Work-Life Balance: Unwind with generous holiday and New Year bonuses.
• Top-Tier Equipment: Stay productive with the latest tools, including a MacBook and iPhone.
• Thriving Culture: Immerse yourself in a dynamic, inclusive work environment that fosters growth.
• Employee Support: Enjoy twice-yearly expense reimbursements for home visits.