Data Engineer

Aston Carter•Atlanta, GA

1d•$60 - $67•Remote

About The Position

The Data Engineer will help develop and modernize the organization’s data environment, creating a clean, reliable, and scalable foundation for reporting, analytics, and future AI and automation initiatives. The role works with large volumes of business and project data, learning existing methodologies and workflows and improving how data is collected, transformed, organized, and delivered across the organization. The Data Engineer uses SQL to develop and troubleshoot complex data transformations, builds and maintains VertiPaq semantic models, and uses DAX for business calculations and reporting. The role also establishes data pipelines and structures that integrate information from multiple systems consistently. It uses programming languages such as Python, R, or Scala and distributed processing engines such as Spark to support large-scale data processing, transformation, and automation. This is a fully remote contract-to-hire position based out of Atlanta, Georgia. Core collaboration is aligned to Eastern or Central Time Zones. The pay range is $60.00–$67.00 per hour. The position is anticipated to close on November 15, 2026.

Requirements

At least 3 years of experience using SQL to develop and troubleshoot complex data transformations.
At least 3 years of experience with VertiPaq semantic modeling, including building and maintaining analytics data models.
At least 3 years of experience using DAX to create and optimize business calculations and support reporting.
At least 3 years of experience using Python, R, or Scala for data processing, transformation, or automation.
At least 3 years of experience using Spark or other distributed data processing engines to manage large-scale data workloads.
At least 3 years of experience developing and modernizing a company’s data environment for reporting, analytics, and automation.
Strong understanding of database concepts and large-scale data architectures.
Ability to analyze and document existing methodologies and workflows and translate them into improved data processes.
Proficiency in designing scalable, reliable, and maintainable data pipelines and data structures.

Responsibilities

Design, develop, and enhance processes to collect, transform, organize, and deliver large volumes of business and project data.
Use SQL to develop, optimize, and troubleshoot complex data transformations for reporting and analytics.
Build, maintain, and improve VertiPaq semantic models for business intelligence and self-service analytics.
Develop and refine DAX calculations for business metrics, reporting requirements, and analytical use cases.
Work with stakeholders to understand existing methodologies and workflows and translate them into efficient, scalable data solutions.
Establish and maintain data pipelines and structures that integrate information from multiple systems consistently and reliably.
Contribute to modernizing the company’s data environment to enable advanced analytics, AI, and automation initiatives.
Use Python, R, Scala, or similar programming languages for data processing, transformation, and automation.
Use Spark or other distributed data processing engines to handle large-scale workloads and improve performance.
Work with business and technical teams to align data models, transformations, and reports with business requirements and industry best practices.