Description

You will design and implement ETL processes using AWS Glue, Python, and SQL to ingest, transform, and load data.

Responsibilities

• Develop and maintain data lakes and data warehouses using Amazon S3 and Amazon Redshift.
• Optimize data storage, performance, and cost efficiency leveraging Redshift Spectrum and query tuning.
• Build reusable data ingestion and transformation frameworks following best practices for scalability and security.
• Troubleshoot performance bottlenecks and ensure system reliability adhering to AWS Well-Architected practices.
• Define data models, governance, and solution design in collaboration with cross-functional teams.

Required Skills

• 6+ years of hands-on experience with the AWS analytics stack, including AWS Glue, Amazon Redshift, and Amazon S3.
• Proficiency in Python for data processing and automation.
• Strong SQL expertise for complex queries, transformations, and data validation.
• Experience with data modeling, schema design, and dimensional modeling (Star/Snowflake schemas).
• Good understanding of data architecture, integration patterns, and solution design principles.
• Exposure to data governance, cataloging, and security best practices within the AWS environment.
• Experience implementing data quality checks and monitoring across ETL pipelines.
• Bachelor's degree.

Key Skills

Education

Bachelor's degree