Data Engineer

• Analytics Engineer
• Miami, FL
• Hybrid: 3 days a week, 2 Days Remote
• $55-$60/hour - depending on Experience
• 3 Month Contract to Hire - this is W-2 only with Brooksource. No open to c2c or 1099

• Job Summary
• We are seeking an Analytics Engineer to support the design, build, and modernization of our enterprise data warehouse. This role will work hands-on in building out an agentic framework, performing data modeling, SQL development, and data validation, and more.
• The ideal candidate brings strong SQL and database expertise, experience analyzing legacy SQL Server environments, and the ability to perform data cleanup and reconciliation during platform conversions. This role sits at the intersection of analytics, data engineering, and technical analysis, requiring both execution and documentation skill

Technical Stack/Must Have:

• AWS
• DBT
• Snowflake
• SQl/Python

• Key Responsibilities
• Data Modeling & Warehouse Development
• Design and implement dimensional data models (fact and dimension tables)
• Build and maintain curated analytics datasets to support reporting and downstream consumption
• Apply data warehousing best practices (star/snowflake schemas, SCD patterns, conformed dimensio
• Write, optimize, and maintain complex SQL transformations
• Current State Analysis & Data Conversion
• Analyze existing SQL Server databases to understand currentstate schemas, relationships, and data us
• Perform data profiling, cleanup, and remediation during data warehouse migration/conversion effo
• Identify data quality issues (duplicates, nulls, type mismatches, integrity gaps) and define resolution
• Reconcile source and target datasets to validate accuracy and completeness
• Data Engineering Collaboration & Specification
• Translate business and analytical requirements into technical specifications for data pipelines, including
• sourcetotarget mapping
• transformation logic
• data quality and validation rules
• acceptance criteria and edge cases
• Partner with Data Engineers during backlog refinement and implementation
• Support testing, validation, and production readiness of data pipelines