
AI Data Engineer
- دبي
- دائم
- دوام كامل
- Design, build, and manage scalable and efficient data pipelines for AI/ML systems.
- Collaborate with AI/ML teams to understand data requirements and deliver high-quality datasets.
- Optimize data storage and retrieval to support low-latency AI workloads.
- Implement ETL/ELT processes using modern data engineering tools and cloud platforms.
- Ensure data quality, consistency, governance, and security across platforms.
- Integrate structured and unstructured data from various sources (APIs, databases, streaming platforms, etc.).
- Work with large-scale distributed systems and big data technologies such as Spark, Hadoop, Kafka, etc.
- Monitor data pipelines for performance and reliability; automate error handling and recovery.
- Contribute to the development and deployment of AI/ML models in production environments.
- Document data processes, schemas, and infrastructure for cross-functional use.
- Bachelor's or Masters degree in Computer Science, Data Engineering, or a related field.
- 5 years of experience in data engineering, preferably with exposure to AI/ML workflows.
- Proficiency in programming languages like Python, Scala, or Java.
- Experience with cloud platforms such as AWS, Azure, or GCP (e.g., S3, Redshift, BigQuery, Databricks).
- Hands-on experience with data orchestration tools (e.g., Apache Airflow, Prefect).
- Proficiency in SQL and NoSQL databases.
- Familiarity with machine learning workflows and tools (TensorFlow, PyTorch, MLflow, etc.) is a plus.
- Knowledge of data lakehouse architectures and MLOps pipelines is desirable.
- Experience with containerization (Docker) and CI/CD pipelines is an advantage.
- Strong problem-solving and analytical thinking skills.
- Ability to work in a fast-paced, collaborative environment.
- Excellent communication skills with both technical and non-technical stakeholders.
- Detail-oriented with a strong sense of ownership and accountability.
- Experience with real-time data processing and stream analytics (Kafka, Flink, etc.).
- Exposure to GenAI or LLM-based applications.
- Certification in cloud or data engineering platforms (e.g., AWS Certified Data Analytics, GCP Data Engineer).