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Title
Text copied to clipboard!Cloud Data Engineer
Description
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We are looking for a highly skilled Cloud Data Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing, implementing, and managing cloud-based data solutions. You will be responsible for developing and maintaining scalable data pipelines, optimizing data storage, and ensuring data security and compliance. Your role will involve collaborating with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions. You will also be expected to stay up-to-date with the latest cloud technologies and best practices to continuously improve our data infrastructure. The successful candidate will have a strong background in cloud platforms such as AWS, Azure, or Google Cloud, and be proficient in programming languages like Python, Java, or Scala. You should also have experience with big data technologies such as Hadoop, Spark, and Kafka. Excellent problem-solving skills, attention to detail, and the ability to work in a fast-paced environment are essential for this role. If you are passionate about data and cloud technologies and are looking for an exciting opportunity to make a significant impact, we would love to hear from you.
Responsibilities
Text copied to clipboard!- Design and implement cloud-based data solutions.
- Develop and maintain scalable data pipelines.
- Optimize data storage and retrieval processes.
- Ensure data security and compliance with industry standards.
- Collaborate with data scientists and analysts to understand data requirements.
- Monitor and troubleshoot data pipeline issues.
- Implement data quality and validation processes.
- Stay up-to-date with the latest cloud technologies and best practices.
- Document data solutions and processes.
- Provide technical support and guidance to team members.
- Participate in code reviews and ensure coding standards are met.
- Automate data workflows and processes.
- Manage cloud resources and optimize costs.
- Develop and maintain ETL processes.
- Implement data governance policies.
- Ensure high availability and disaster recovery of data solutions.
- Perform data migration and integration tasks.
- Collaborate with cross-functional teams to deliver data solutions.
- Conduct performance tuning and optimization of data solutions.
- Provide training and support to end-users.
Requirements
Text copied to clipboard!- Bachelor's degree in Computer Science, Information Technology, or related field.
- 3+ years of experience in cloud data engineering.
- Proficiency in cloud platforms such as AWS, Azure, or Google Cloud.
- Strong programming skills in Python, Java, or Scala.
- Experience with big data technologies such as Hadoop, Spark, and Kafka.
- Knowledge of SQL and NoSQL databases.
- Familiarity with data warehousing concepts and technologies.
- Experience with ETL tools and processes.
- Strong understanding of data security and compliance.
- Excellent problem-solving and analytical skills.
- Ability to work in a fast-paced environment.
- Strong communication and collaboration skills.
- Experience with containerization and orchestration tools like Docker and Kubernetes.
- Knowledge of data governance and data quality best practices.
- Experience with version control systems like Git.
- Ability to write clean, maintainable, and efficient code.
- Strong attention to detail and accuracy.
- Ability to manage multiple tasks and projects simultaneously.
- Experience with monitoring and logging tools.
- Familiarity with machine learning and AI concepts is a plus.
Potential interview questions
Text copied to clipboard!- Can you describe your experience with cloud platforms such as AWS, Azure, or Google Cloud?
- How do you ensure data security and compliance in your data solutions?
- Can you provide an example of a complex data pipeline you have developed?
- How do you approach optimizing data storage and retrieval processes?
- What big data technologies are you most familiar with?
- How do you handle data quality and validation in your projects?
- Can you describe a time when you had to troubleshoot a data pipeline issue?
- How do you stay up-to-date with the latest cloud technologies and best practices?
- What is your experience with ETL tools and processes?
- How do you collaborate with data scientists and analysts to understand data requirements?
