Our client is seeking an Enterprise Data Warehouse Lead with expertise in Redshift & Boomi. If interested, please apply! Please NO 3rd Parties, only direct candidates!

About the Opportunity:

• Location: Fully Remote (supporting East Coast client)
• Hours: 9-5, Full Time (40 hours/week)

Responsibilities:

• Architect a new Enterprise Data Warehouse using Redshift as the Data Lake, Boomi for ETL, Power BI and Tableau for reporting.
• Implement new Data Lake with Redshift for Manufacturing (MES) and Regulatory data reporting.
• Create efficient data models and database schemas within Redshift, considering data redundancy, normalization, and performance optimization for complex queries.
• Analyze and optimize complex SQL queries to improve query performance and scalability on large datasets within Redshift, leveraging indexing strategies and query optimization techniques.
• Implement data security measures within Redshift to protect sensitive information, adhering to data privacy regulations and access control policies.
• Identify and resolve performance bottlenecks in Redshift queries, analyzing execution plans and proposing improvements to data storage and processing.
• Design and implement robust ETL (Extract, Transform, Load) processes to integrate data from diverse sources into the Redshift data warehouse, ensuring data quality and consistency.
• Create comprehensive technical documentation for data warehouse architecture, data models, and key performance indicators.

Qualification:

• Amazon Redshift expertise with a deep understanding of Redshift architecture, data loading mechanisms, query optimization techniques, and best practices for managing large-scale Experience with Boomi for ETL
• Ideal candidate will have worked independently in smaller environments
• Some experience supporting Pharma or Medical Device clients in a GMP environment
• Experience with data visualization tools (e.g., Tableau, Power BI)
• Familiarity with data security and privacy best practices
• Proficient in SQL with extensive experience writing complex SQL queries for data manipulation, aggregation, and analysis within a relational database environment.