Cloud Engineer
4 weeks ago
Aws+Databricks Cloud Data Engineer
Design and Develop Data Pipelines:
• Create robust and scalable data pipelines using Apache Spark for data extraction, transformation, and loading (ETL).
• Collaborate with cross-functional teams to understand data requirements and translate them into efficient pipeline designs.
• Optimize data workflows for performance, reliability, and scalability.
• Cloud-Based Data Solutions leveraging AWS services to build and manage data infrastructure.
• Implement data storage solutions, ensuring data security, availability, and cost-effectiveness.
• Work experience with Databricks for data processing
• Data Modeling and Schema Design:
• Design and maintain data models, ensuring data consistency, integrity, and accuracy.
Performance Optimization:
• Identify bottlenecks and optimize data processing performance.
• Tune Spark jobs, optimize SQL queries, and improve data pipeline efficiency.
• Document data pipelines, workflows, and architectural decisions.
Mandatory skills- AWS Services, Spark, Databricks, SQL
Apache Spark: Hands-on experience with Spark for data processing and analytics.
• AWS: Familiarity with AWS services for data storage, compute, and analytics.
• Databricks: Experience working with Databricks for big data processing.
• Problem-Solving Skills: Ability to troubleshoot complex data issues and optimize data workflows.
Strong Communication Skills: Collaborate effectively with cross-functional teams and articulate technical concepts to non-technical stakeholders
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