A.I. Data Engineer

Key Responsibilities Design, develop, and maintain scalable and robust data architecture. Create and manage databases, data processing systems, and data integration solutions. Develop and implement efficient ETL processes for data ingestion and transformation. Ensure data quality and integrity throughout the ETL pipeline. Design and implement data models for optimal storage and retrieval. Build and maintain data warehouses for analysis and reporting purposes. Monitor and optimize database performance. Troubleshoot and resolve data-related issues in a timely manner. Work with stakeholders to understand data requirements and translate them into effective database structures. Implement and enforce data security measures and compliance standards. Collaborate with cross-functional teams, including AI Engineer, Data Scientists, Data Analysts, Software engineers and DevOps. Requirements: Bachelor's degree or higher education qualification in Computer Science, Software Engineering, or a related field  Proven experience as a Data Engineer or similar role. Able to speak in English and Mandarin. Hands-on experience with data warehousing, ETL processes, and database management. Proficiency in SQL and one or more programming languages (e.g., Python, Java, JavaScript). Knowledge of data modelling and database design principles. Strong proficiency with ETL tools such as Apache Airflow and Dagster. Familiarity with Big Data technologies (e.g., Hadoop, Spark). Understanding of data governance principles and practices. Nice to have: Exposure to machine learning concepts and integration of machine learning models into data pipelines. Familiarity with containerization tools like Docker and orchestration tools like Kubernetes. Knowledge of streaming data technologies (e.g., Apache Kafka). Experience with cloud platforms such as AWS, Azure, or Google Cloud.
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