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Analytics Engineer; Redshift, Data Warehousing, SQL Server

Job in Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listing for: Brooksource
Full Time, Part Time position
Listed on 2026-10-18
Job specializations:
  • IT/Tech
    Data Warehousing, Data Engineering, Data Analyst
Salary/Wage Range or Industry Benchmark: 60 - 70 USD Hourly USD 60.00 70.00 HOUR
Job Description & How to Apply Below

Analytics Engineer (Redshift, Data Warehousing, SQL Server)

Charlotte, NC

Hybrid position (3 days per week onsite in uptown Charlotte)

Compensation: $60 – $70 per hour (W-2 only; no Corp-to-Corp or 1099 arrangements)

1-year contract with opportunity for extension or full-time hire

Applications accepted through October 22, 2026

ABOUT

THE ROLE

Brooksource is seeking an Analytics Engineer to support the modernization and ongoing development of enterprise data warehouse solutions for our Fortune 500 client. In this hybrid role based in Charlotte, NC, you will focus on designing and implementing dimensional data models, developing complex SQL transformations in Amazon Redshift, and supporting data migration efforts from legacy SQL Server environments. The ideal candidate combines strong data warehousing expertise with advanced SQL skills and the ability to analyze, cleanse, reconcile, and validate enterprise data.

You will serve as a key liaison between business stakeholders, analytics teams, and Data Engineers, translating requirements into clear technical specifications that enable scalable and trusted data solutions. This position requires hands‑on experience with Amazon Redshift, data modeling, data quality remediation, and data warehouse modernization initiatives. You will work across both business and technical teams to deliver reliable analytics capabilities and enterprise reporting solutions.

WHAT

YOU'LL DO
  • Design and implement dimensional data models, including fact and dimension tables, within Amazon Redshift
  • Build and maintain curated analytics datasets to support reporting, business intelligence, and downstream analytical use cases
  • Apply data warehousing best practices including star schemas, snowflake schemas, slowly changing dimensions, and conformed dimensions
  • Write, optimize, and maintain complex SQL queries and transformations to support analytics and reporting requirements
  • Analyze existing SQL Server databases to understand source data structures, relationships, and business rules
  • Perform data profiling, cleansing, remediation, and reconciliation activities during data warehouse migration and modernization efforts
  • Identify and resolve data quality issues including duplicates, null values, data type inconsistencies, and integrity concerns
  • Validate migrated data through source-to-target reconciliation and testing processes
  • Translate business and analytical requirements into technical specifications, source-to-target mappings, transformation logic, and validation criteria
  • Partner closely with Data Engineering teams to support backlog refinement, pipeline development, and production readiness activities
  • Create and maintain data dictionaries, technical documentation, transformation specifications, and data model documentation
  • Collaborate with business stakeholders, analysts, and engineering teams to ensure data solutions align with organizational needs
  • Support testing, validation, and deployment efforts for new data warehouse capabilities and enhancements
WHAT YOU BRING
  • Bachelor's degree in Computer Science, Information Systems, Analytics, Engineering, or a related field, or equivalent professional experience
  • 4-7 years of experience in analytics engineering, data warehousing, data modeling, or related data-focused roles
  • Strong hands‑on experience with Amazon Redshift or comparable cloud-based data warehouse platforms
  • Advanced SQL experience including complex joins, aggregations, window functions, and query performance optimization
  • Experience working with SQL Server databases, particularly within legacy modernization or migration initiatives
  • Strong understanding of dimensional modeling and enterprise data warehouse design principles
  • Experience supporting ETL/ELT processes and collaborating with Data…
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