Top Data Engineer Jobs in Atlanta, GA

Design, implement, and manage advanced data ecosystems and scalable ETL/ELT pipelines. Analyze complex problems, deliver data warehousing and governance solutions, mentor junior staff, and build client relationships while maintaining high standards and business-context awareness.

Lead and manage delivery of modern data ecosystems and managed data analytics programs. Oversee project planning, budgeting, quality, and client accounts. Mentor teams, drive data strategy, convert insights to business opportunities, and ensure standards and risk management across large transformations.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Design and build data infrastructure and pipelines using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, collaborate with clients, and apply data architecture, transformation, and analytics to deliver insights.

Develop and maintain data pipelines and ETL processes, optimize SQL and data architectures, build BI reports and dashboards (Oracle BI, QlikView, Spotfire), analyze data to produce strategic insights, support client engagements in regulated environments, and apply continuous process improvements to ensure data quality and integrity.

Designs, builds, and maintains moderately complex cloud-based data systems, streaming and batch pipelines, and data infrastructure. Partners with stakeholders to implement scalable data formats, models, deployment pipelines, and prototypes to support analytics and reporting.

Lead development and delivery of data engineering solutions for clients: design data architectures, build and maintain ETL pipelines, apply advanced analytics, implement BI visualizations, coach teams, manage managed-services SLAs, and engage stakeholders to validate and refine outcomes.

Lead data engineering engagements delivering ETL/ELT solutions, pipelines, and cloud analytics. Build and maintain architectures (DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate/CDC, S3/Glue), oversee BI and visualization, manage client accounts and teams, mentor junior staff, ensure project delivery and quality, and drive process and technology adoption.

The Data Engineer will develop cloud-based data pipelines, collaborate with clients on data architecture, and utilize engineering best practices to provide effective data solutions.

Design, build, and maintain scalable batch and streaming data pipelines. Write clean code (Python, SQL, Spark), ensure data quality and reliability, monitor and troubleshoot pipelines, document sources and transformations, and collaborate with analysts, data scientists, and product teams to deliver data products and support analytics and ML use cases.

Design, build, and operate scalable finance data pipelines and analytics-ready datasets. Support ELT/ETL, data quality, governance, semantic models, Power BI reporting, forecasting, ARR analytics, and AI-enabled analytics. Partner with finance stakeholders to translate requirements and maintain production-grade, monitored data solutions.

Lead design, build, and maintain scalable data pipelines, ETL processes, data models, and storage solutions. Support production data ecosystem, optimize performance, ensure data quality and security, integrate data sources/APIs, and provide technical guidance to teams while collaborating with stakeholders.

Design, build, operate, and support ETL/ELT pipelines, integrations, and curated datasets across enterprise systems (Salesforce, Deltek, Autodesk, Azure, Microsoft Fabric). Implement data models, orchestration, API-first services, data quality, governance, and monitoring to support BI, reporting, AI/ML, and secure data delivery.

Design, develop, and maintain scalable data pipelines, warehouses, and stores. Build ETL/ELT workflows, process structured and unstructured data with SQL and Python, validate databases, and support data platform scaling, monitoring, and operations for mission-driven clients.

Design, build, and maintain the U.S. data platform and end-to-end integrations (customers, 3PLs, SAP/OMS/TMS/WMS/CRM). Implement data warehouse architecture, data models, governance, metadata, lineage, and quality monitoring to support BI, AI, self-service analytics, and reporting while aligning with global standards.

The Data Engineer role involves developing and maintaining data pipelines for forecasting in commercial real estate, ensuring data integrity and supporting analytics teams.

Build, deploy, and operate Azure-based data integration and analytics solutions using Databricks, Delta Lake, ADF, and Synapse. Implement ingestion, transformation, data models, governance, performance optimization, CI/CD, and MLOps patterns while collaborating with architects, offshore teams, and business stakeholders.

The Data Engineer will develop data pipelines, support Agile teams, ensure data performance, and collaborate to implement complex requirements for federal customers.

The Principal Data Engineer leads the development of scalable data solutions, collaborates on product roadmaps, influences organizational change, and coaches junior staff in a hybrid work environment.

Lead the design and migration of a data platform architecture. Manage data pipelines, mentor teams, and ensure platform reliability.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Build and maintain Azure Data Factory ingestion pipelines into Snowflake, implement medallion transformations (Coalesce), write Python orchestration and connectors, apply governance with Atlan, collaborate with AI coding agents, participate in CI/CD with Azure DevOps, handle on-call production support, and document runbooks.

As a Data Engineer, you'll deliver scalable data solutions, participate in technical discussions, and ensure timely, trustworthy data delivery through robust pipelines.