Cloud Data Engineer

Key Skills

Apache Airflow, Automation, Azure, Effective communication skills, ETL/ELT technologies, Kubernetes-K8s, Python Programming, Snowflake

Job Description

Responsibilities:

• Design, implement, and optimize end-to-end data pipelines in cloud and on-prem environments.
• Utilize Kubernetes for efficient container orchestration and deployment of data applications.
• Develop and maintain Python-based scripts and code for data processing and transformation.
• Leverage Snowflake for managing and enhancing data warehousing capabilities.
• Implement, manage, and troubleshoot data workflows using Apache Airflow.
• Conduct thorough data analysis to extract valuable insights and support decision-making processes.
• Utilize Azure services for cloud data solutions and integrations.

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, or a related field.
• Proven experience in cloud data engineering, demonstrating a strong understanding of data architecture and best practices.
• Proficient in Python for data manipulation, scripting, and automation.
• Hands-on experience with Kubernetes for containerized application deployment.
• Expertise in Snowflake for effective data warehousing and analytics.
• Expertise with Apache Airflow for workflow automation and orchestration.
• Experience with Azure cloud services for data solutions and integrations.
• Solid background in data analysis, utilizing tools and techniques to derive meaningful insights.
• Strong problem-solving skills and the ability to troubleshoot complex data issues.
• Effective communication skills to collaborate with cross-functional teams.
• Proactive in staying abreast of industry trends and advancements in cloud data engineering.
• Experience with traditional ETL tools like Datastage and scheduling tools like Control-M a plus.

If you possess these qualifications and are eager to contribute to a dynamic team, please submit your resume outlining your relevant experience.