AWS Data Engineer (Senior)

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• Type of role: 100% Full-time remote

Our client, they are looking for a Senior AWS Data Engineer to join our team. The ideal candidate should have extensive experience in PySpark and SQL, and hands-on expertise in building data pipelines using Amazon EMR or Amazon Glue. This role requires a strong background in data modeling, querying with Amazon Redshift, Snowflake, Athena, Presto, and orchestration using Apache Airflow.

Responsibilities:

• Develop and maintain data pipelines using Amazon EMR or Amazon Glue.
• Design data models and support end-user querying with Amazon Redshift, Snowflake, Athena, and Presto.
• Build and manage the orchestration of data pipelines using Apache Airflow.
• Collaborate with cross-functional teams to understand data needs and design optimal solutions.
• Troubleshoot and optimize data pipelines and data models for performance and scalability.
• Write and maintain PySpark and SQL scripts for ETL processes.
• Document and communicate technical solutions to both technical and non-technical stakeholders.
• Stay updated with new AWS data technologies and assess their impact on existing systems.

Requirements:

• Bachelors degree in Computer Science, Engineering, or a related field.
• 3+ years of experience working with PySpark and SQL.
• 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue.
• 2+ years of experience with data modeling and querying using Amazon Redshift, Snowflake, Athena, and Presto.
• 1+ year of experience building and managing data pipeline orchestration using Apache Airflow.
• Strong problem-solving and troubleshooting skills.
• Excellent communication and collaboration abilities.
• Ability to work independently and in a team-oriented environment.

Preferred Qualifications:

• AWS Data Analytics Specialty Certification.
• Experience with Agile development methodologies.