We are seeking a highly experienced Data Engineer to join our client and play a critical role in shaping our data infrastructure and driving innovative solutions. This individual will work closely with a talented Data Science team and contribute to cutting-edge AI projects. The ideal candidate is an expert in building and optimizing data pipelines, designing scalable architectures, and ensuring seamless data flow to support complex analytics and AI initiatives.
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Responsibilities:
- Data Architecture and Pipelines: Design, implement, and optimize robust data pipelines for large-scale data ingestion, transformation, and storage. Work with real-time and batch data processing frameworks such as Apache Spark, Apache Kafka, and Apache NiFi.
- Collaboration with Data Science and AI Teams: Partner with data scientists and AI engineers to build efficient data workflows and deliver high-quality data for model development and analytics. Develop infrastructure to support machine learning and AI model deployment.
- Data Integration and Storage: Manage and optimize Data Lakes and data warehouses, ensuring seamless integration and accessibility. Leverage Apache Iceberg for scalable, high-performance table formats in large-scale analytics.
- IBM Technology Stack: Work extensively with IBM products such as IBM DataStage, IBM Db2, IBM Watson, and other relevant tools. Integrate and optimize IBM technologies to enhance data management and AI-driven solutions.
- Graph and NoSQL Databases: Design and maintain data models using Neo4j for graph database applications. Manage and query NoSQL databases like MongoDB to support diverse data structures.
- Data Governance and Security: Ensure compliance with data security standards and best practices. Establish frameworks for data quality, metadata management, and data governance.
- Performance Optimization: Troubleshoot and resolve data-related issues to maintain high system performance and reliability. Continuously improve system architecture to enhance scalability and efficiency.
Required Skills:
- AI Integration: Demonstrated ability to collaborate with Data Science teams on AI and ML projects.
- Programming: Strong skills in Python, Java, or Scala for data processing and pipeline development.
- Cloud Expertise: Familiarity with cloud platforms (AWS, Azure, GCP) is a plus.
- Language Requirements: Fluent in Arabic (mandatory).
Required Experience:
- Minimum of 5 years in data engineering or a related role, with proven experience in data-intensive environments and AI projects.
- Minimum of 3 years in Data Lakes.
- Extensive experience with IBM products (e.g., IBM DataStage, IBM Db2, IBM Watson).
- Strong knowledge of Data Lakes and Apache Iceberg.
- Proficiency with Apache Spark, Apache Kafka, and Apache NiFi for large-scale data processing.
- Expertise in Neo4j and other graph databases.
- Hands-on experience with MongoDB and NoSQL databases.
Required Education:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
