Data Engineer (Dubai)

freeC's Client

• 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.

Job requirement

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

• Assistance with accommodation, living expenses, and work visa procurement for all staff.
• Financial assistance for employees to visit home fourth a year.
• A salary package that reflects your skills, experience, and contributions to the company.
• Provision of necessary work equipment, including a MacBook and iPhone.
• Continuous development of hard and soft skills through work and professional training.
• A holiday and New Year bonus to recognize your hard work and dedication.
• A professional, dynamic, and inclusive workplace culture that fosters collaboration and innovation.