Top Hybrid Data Engineering Jobs in Atlanta, GA

Lead data engineering efforts within Technology Consulting: design data architecture and pipelines, implement AWS/Redshift and ETL solutions, support BI (QlikView/Oracle BI), coach teams, manage client relationships and SLAs, apply systems thinking to optimize outcomes and validate solutions with stakeholders.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

Entry-level Data Engineer responsible for building and maintaining cloud-based data assets and pipelines, improving data quality and automation, investigating data integrity issues, and collaborating with architects, analysts, and stakeholders. Uses SQL and Python, participates in Agile practices, leverages AI-powered developer tools for spec-driven development, and follows responsible AI and data privacy practices.

The Manager for Data Engineering will lead the Data & AI team, focusing on building modern data platforms, providing mentorship, and overseeing project delivery using Microsoft technologies.

Build, operate, and monitor ETL/ELT pipelines between marketing, sales, and operational systems into Databricks. Implement dimensional models, identity resolution, data quality checks, API integrations, and scheduled/event-driven syncs to support segmentation, attribution, and campaign activation. Maintain documentation, alerting, and runbooks.

The Global Indirect Tax Automation Manager will manage third-party tax systems and custom billing system implementations, focusing on requirements gathering, design, build, and testing.

Seeking a CommVault Systems Engineer to design, configure, troubleshoot, and support backup and recovery solutions in a federal environment, ensuring compliance with security requirements.

Design and implement cloud-native Azure data architectures, data models, ELT processes, governance, and security. Collaborate with engineering, BI, and data science teams to optimize pipelines, ensure data quality, document designs, and support system stabilization for analytics and operational use cases.

As a Lead Data Engineer, you will architect data foundations for AI applications, lead a team, optimize data pipelines, and ensure data governance.