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You will be updated with latest job alerts via emailHiring for Trainer profile for Data EngineerData Architecture and Design: Develop and maintain data architectures including data models data warehouses and data lakes to support AI and machine learning initiatives.Data Pipeline Development: Design and implement data pipelines to extract transform and load (ETL) data from various sources into a centralized system where it can be used for AI applications.Data Integration: Integrate data from multiple sources including databases APIs and external data feeds ensuring that data is consistent accurate and accessible.Data Quality Management: Monitor and ensure the quality of data implementing validation checks and cleaning processes to maintain high standards of data integrity.Performance Optimization: Optimize data processing workflows and queries to improve the performance of data pipelines and support efficient AI model training and inference.Collaboration with Data Scientists: Work closely with data scientists and machine learning engineers to understand data requirements facilitate data access and provide support for the development and deployment of AI models.Data Security and Privacy: Implement data security measures and ensure compliance with privacy regulations to protect sensitive information and maintain data confidentiality.Scalability and Maintenance: Ensure data infrastructure is scalable to handle growing data volumes and perform routine maintenance to keep systems running smoothly.Documentation and Reporting: Document data engineering processes architectures and pipelines and generate reports to communicate data insights and system performance to stakeholders.Technology Evaluation and Adoption: Stay uptodate with emerging technologies and tools in the data engineering and AI space evaluating their potential benefits and integrating them into existing systems as appropriate.
Full Time