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.
