Description

You will design, build, and optimize scalable data pipelines and warehouses on AWS.

This role is remote.

Responsibilities

• Design and implement ETL processes using AWS Glue, Python, and SQL for data ingestion, transformation, and loading.
• Develop and maintain data lakes and warehouses on Amazon S3 and Amazon Redshift, ensuring scalability and security.
• Optimize data storage, performance, and cost efficiency using Redshift Spectrum and query tuning.
• Define data models, governance standards, and solution designs in collaboration with cross-functional teams.
• Troubleshoot performance bottlenecks and ensure system reliability adhering to AWS Well-Architected practices.

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, automation, and building reusable frameworks.
• 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.

Preferred Skills

• Familiarity with Tableau and DataIQ for data analytics and visualization.

Bachelor's degree required.

Key Skills

Education

Bachelor's degree