A cloud data engineer is a professional responsible for designing, building, and maintaining cloud-based data infrastructure and data pipelines. They work with various data management systems and tools, such as AWS, Google Cloud, Microsoft Azure, or other cloud-based technologies, to develop, implement, and manage data pipelines that can process, store, and retrieve large amounts of data.

The job description for a cloud data engineer typically includes the following responsibilities:

· Designing and building cloud-based data infrastructure and data pipelines using cloud services such as AWS, Google Cloud, or Microsoft Azure.

· Developing, testing, and deploying data integration processes that move data from various sources into cloud-based data warehouses or data lakes.

· Collaborating with data scientists, business analysts, and other stakeholders to identify data requirements and develop appropriate data solutions.

· Implementing and managing data governance policies, data quality, and data security measures to ensure data accuracy, consistency, and privacy.

· Managing and monitoring cloud-based data infrastructure and data pipelines to ensure data availability, scalability, and reliability.

· Troubleshooting and resolving issues related to data pipelines and data infrastructure.

· Keeping up-to-date with emerging trends and technologies in cloud-based data engineering and integrating them into existing data pipelines and infrastructure.

· Developing documentation and training materials for end-users to ensure they can effectively use the cloud-based data infrastructure and data pipelines.

The ideal candidate for this role should have:

· A degree in computer science, data engineering, or a related field.

· Hands-on experience with cloud-based data engineering tools such as AWS, Google Cloud, or Microsoft Azure.

· Strong programming skills in languages such as Python, Java, or Scala.

· Knowledge of data management systems, such as SQL, NoSQL, and Hadoop.

· Experience with data integration and ETL processes.

· Understanding of data governance, data quality, and data security best practices.

· Strong problem-solving and analytical skills.

· Good communication and collaboration skills to work effectively with different stakeholders.