Sales Analytics Partner III (EMEA)
IT Services and IT Consulting Company Dubai, United Arab Emirates
Unlock employer Abu Dhabi, United Arab Emirates Posted: 07 Mar 2025
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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Unlock employer & apply directlyWork Conditions: Full-time, On-site (Abu Dhabi Emirate, United Arab Emirates)
Responsibilities:
Data Architecture and Pipelines: Design, implement, and optimize robust data pipelines to handle 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.
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