AWS Redshift Subject Matter Expert (SME)

About

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Position Description

• AWS Redshift Subject Matter Expert (SME) will be providing deep technical leadership, optimization, and strategic guidance for an organization cloud data warehousing solutions, covering both Provisioned and Serverless deployments.
• This role requires a blend of hands-on technical skills, architectural oversight, and strong communication to ensure Redshift environments are scalable, cost-efficient, and highly performant.

Education

This position requires a Bachelor s in Computer Science, Information Systems, or a related field or equivalent work experience. (Note: A Master s degree is preferred.)

Architectural & Strategic Leadership

• Solution Design: Architect, design, and implement scalable, secure, and cost-effective data warehousing solutions using both Redshift Provisioned and Redshift Serverless.
• Deployment Strategy: Determine the optimal deployment model (Provisioned vs. Serverless) for various workloads, considering factors like predictability, cost, concurrency, and required fine-grained control.
• Modernization: Lead efforts to modernize existing on-premises or cloud data warehouses (e.g., Teradata, Snowflake, etc.) to AWS Redshift, including developing migration strategies and execution plans.
• Integration: Define and implement integration patterns with the broader AWS ecosystem, including Amazon S3 (for Redshift Spectrum/Data Lake), AWS Glue, Amazon Kinesis, Amazon EMR, and machine learning services (Redshift ML).

Performance and Optimization

• Query Tuning: Expertly analyze, optimize, and refactor complex SQL queries for maximum performance and cost efficiency, utilizing features like Workload Management (WLM) in Provisioned clusters and capacity settings in Serverless.
• Design Optimization: Tune data warehouse performance by implementing best practices for data distribution keys, sort keys, and compression encodings for both Provisioned nodes (RA3) and Serverless data.
• Monitoring and Troubleshooting: Establish and manage advanced monitoring using Amazon CloudWatch and Redshift system tables to preemptively identify and resolve performance bottlenecks, resource contention, and system failures.
• Cost Management: Implement effective cost controls, managing node types/reserved instances for Provisioned clusters and defining Redshift Processing Units (RPUs) capacity and usage limits for Serverless environments to ensure predictable spending.

Data Governance and Operations

• Security: Enforce enterprise-level data security, including implementing encryption (at rest and in transit), managing access control via AWS IAM and database user management, and configuring VPC endpoints.
• High Availability & Disaster Recovery (HA/DR): Define and implement backup/restore strategies using snapshots, cross-region replication, and leverage the inherent HA features of Redshift Serverless and Multi-AZ for Provisioned.
• Data Modeling & ETL/ELT: Advise on and implement best-practice data models (e.g., Dimensional, Data Vault) and design efficient Extract, Transform, and Load (ETL)/Extract, Load, and Transform (ELT) pipelines.