Top Senior Data Engineer Jobs in Atlanta, GA

Design, build, and maintain scalable cloud and hybrid data platforms, ETL/ELT pipelines, and data models. Implement CI/CD and DevOps practices, ensure data quality, security, and governance, optimize production pipelines, mentor junior engineers, and support data modernization and migration efforts for analytics and operational workloads.

Design and implement AI-optimized data platforms and production ETL/ELT pipelines, build semantic and analytical layers, write production-ready SQL/Python code, collaborate with stakeholders and analytics teams, and contribute to the firms data engineering practice and client delivery.

Lead and deliver AI-optimized data engineering solutions: design cloud data platforms, build ELT/ETL pipelines, implement semantic/analytic layers, write production SQL/Python/Spark code, apply AI-assisted tooling, and lead small teams on client engagements.

Build and maintain governed, activation-ready marketing data products in Snowflake. Design canonical marketing data models, event-streaming, identity resolution, quality checks, and reverse-ETL activation for marketing, CRM, paid media and AI use-cases. Enable predictive scoring, attribution, and AI-ready context layers while partnering with cross-functional stakeholders.

Design, build, and maintain data warehouses, data marts, and OLAP solutions; develop ETL frameworks, data models, SSIS/SSAS/SSRS artifacts, and performance-tuned SQL Server databases to support analytics and visualization projects.

Design, develop, and support Big Data solutions on Teradata Aster and Hadoop platforms. Build ETL pipelines, data mining, reporting, and predictive analytics; write efficient code for large/unstructured datasets; translate business use cases to production; mentor users; contribute to Big Data roadmap and standards.

The Sr. ETL Informatica Systems Engineer develops ETL applications for the EDW/BI program using Informatica tools, managing complex SQL and APIs.

Design, implement, and maintain automated data testing and validation frameworks to ensure data integrity across ETL/ELT pipelines and reporting. Develop reconciliation, profiling, and automated test scripts; embed quality controls into Snowflake, Oracle, and AWS pipelines; support test environment strategy and governance; collaborate with engineers, QA, and stakeholders to improve DataOps, monitoring, and reporting validation while mentoring junior team members.