Job Categories: DevOps
Job Types: Full Time - Work from office
Job Locations: India

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.

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