Job Description \| • Design, build, and operate scalable and secure analytical data platforms with a strong focus on AWS Redshift. • Architect Redshift environments (serverless and provisioned), including decisions around cost, scalability, performance, and workload patterns. • Optimize Redshift performance through query tuning, distribution styles, sort keys, workload management, and capacity planning. • Implement monitoring and observability using AWS CloudWatch and related tooling to proactively manage performance and reliability. • Enable governed data access through data cataloging, role\-based access, audits, and security controls. • Work closely with data processing, ingestion, and architecture teams to support the medallion (bronze/silver/gold) architecture, with emphasis on the gold layer. • Apply data governance practices using AWS Lake Formation, IAM, and related services. • Develop and maintain Python\-based automation and infrastructure\-as\-code (Terraform) to support platform operations. • Support ongoing operations of the Data Distribution Center, ensuring stability of analytics services for downstream teams. • Evaluate and evolve platform capabilities while balancing legacy tooling with future\-state architecture. Required Qualifications • 6\+ years of experience in data engineering, analytics engineering, or platform engineering roles. • Strong hands\-on experience with AWS Redshift, including architecture, scaling, monitoring, and performance optimization. • Advanced SQL skills (complex joins, window functions, performance tuning). • Solid experience with Python for data workloads, automation, or platform tooling. • Deep familiarity with AWS core services (S3, IAM, CloudWatch, KMS, networking concepts such as VPCs and security groups). • Experience implementing data governance, security, and access controls using tools such as AWS Lake Formation and IAM. • Understanding of cloud cost management, scalability tradeoffs, and operational best practices.
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