This is a remote position.

Key Responsibilities

• Optimize and modernize Amazon Redshift environments, including consolidation into Redshift Managed Storage (RMS).
  

• Lead or support migration from Provisioned Redshift to Redshift Serverless with zero or minimal downtime.
  

• Analyze and tune Redshift SQL for performance across batch and ad-hoc analytical workloads.
  

• Review and enhance data ingestion pipelines from AWS sources such as RDS, DynamoDB, and Kinesis.
  

• Design data delivery into Apache Iceberg tables and Redshift with minimal duplication and high efficiency.
  

• Collaborate with stakeholders on architecture recommendations and best practices.
  

Required Skills

• Strong hands-on experience with Amazon Redshift (Provisioned, Serverless, RMS).
  

• Deep SQL performance tuning and query optimization expertise.
  

• Solid AWS data engineering background (RDS, DynamoDB, Kinesis).
  

• Experience with modern lakehouse concepts, especially Apache Iceberg.
  

• Data architecture and analytical platform design experience.
  

Nice to Have

• Exposure to AI-assisted query optimization or analytics platforms.
  

• Experience building or supporting BI and analytics use cases at scale.