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Data Engineer (m/f/d)
Contract
Abu Dhabi, United Arab Emirates
25.06.2026
Role Overview We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. This role focuses on enabling reliable data access, improving data quality, and supporting analytics, reporting, and AI/ML initiatives. The ideal candidate is passionate about working with large datasets and modern data platforms.
Key Responsibilities
Design, build, and maintain scalable data pipelines and ETL/ELT processes.
Develop and manage data architectures, including data lakes, warehouses, and data marts.
Ensure data quality, integrity, and consistency across systems.
Collaborate with data scientists, AI engineers, analysts, and business stakeholders.
Optimize data pipelines and workflows for performance and cost-efficiency.
Implement data governance, security, and compliance best practices.
Monitor data systems, troubleshoot issues, and ensure high availability.
Integrate data from multiple sources including APIs, databases, and streaming platforms.
Maintain documentation for data pipelines, systems, and processes.
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
5+ years of experience in data engineering or a related role.
Strong programming skills in Python, Java, or Scala.
Proficiency in SQL and working with relational and non-relational databases.
Experience with big data technologies such as Apache Spark, Hadoop, or similar.
Hands-on experience with ETL/ELT tools and orchestration frameworks (e.g., Airflow).
Familiarity with cloud platforms such as Azure, AWS, or Google Cloud.
Strong understanding of data modeling and database design principles.
Basic knowledge of AI engineering concepts and ML workflows.
Preferred Qualifications
Highly preferred: Experience working with Databricks.
Experience with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Azure Synapse).
Knowledge of streaming technologies (e.g., Kafka, Kinesis).
Experience with containerization and orchestration tools (Docker, Kubernetes).
Exposure to CI/CD pipelines and DevOps practices.
Familiarity with supporting ML/AI use cases (feature engineering, data pipelines for models).
Key Skills
Strong problem-solving and analytical thinking
Attention to detail and data accuracy
Effective communication and collaboration skills
Ability to work in a fast-paced, data-driven environment
