Top Data Engineer Jobs in Atlanta, GA

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Lead design and implementation of data infrastructure, pipelines, and integrations using cloud platforms. Manage teams and client accounts, ensure data quality, security, and compliance, deploy scalable solutions (Databricks, Snowflake), mentor junior staff, and identify data-driven business opportunities.

Senior Data Engineer on PwC's Managed Data, Analytics & Insights team to design, build and manage advanced data ecosystems. Responsibilities include designing data solutions and scalable pipelines, solving complex problems, mentoring junior staff, maintaining high delivery standards, and building client relationships while aligning solutions to business context.

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

As a Manager in Managed Services, you'll lead data ecosystems projects, mentor juniors, manage client accounts, and deliver data strategies to optimize operations and drive insights for clients.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

The Senior Data Engineer designs and maintains data systems, develops data pipelines for ingestion and analysis, and optimizes data architecture to support business needs.

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.

Design, build, test, and operationalize complex data pipelines and transformations using ETL tools and cloud platforms. Ensure data quality, governance, and security while collaborating across teams, troubleshooting incidents, and mentoring engineers to deliver scalable data solutions for analytics and ML.

As a Data Engineer, you'll build data solutions, analyze sources, support data governance, and educate end users on data products.

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, 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.

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 data engineering engagements to design, build, and maintain ETL/ELT pipelines and cloud data architectures. Manage client accounts and mentor teams, leverage tools like DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate, and BI/visualization platforms to deliver analytics, performance tuning, and scalable reporting solutions.

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

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.

Design, build, and maintain scalable data systems and pipelines (batch and streaming); perform complex data modeling and transformations; implement data architectures, governance, and automated deployment pipelines; collaborate with analytics and stakeholder teams to deliver robust, production-ready data products supporting trading and agricultural analytics.

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.

Design, build, and maintain enterprise data engineering solutions and ETL/ELT pipelines using ADF, SSIS, and SAP Data Services. Develop and optimize database schemas and complex SQL in Oracle and SQL Server, implement data warehouse/data lake architectures (star/snowflake), ensure data quality and governance, create Power BI reports, automate workflows with Python and Shell, troubleshoot pipeline failures, support SDLC, and mentor junior engineers.

Design, build, and optimize cloud data platforms using Azure, Databricks, and Fabric. Lead discovery, architecture, and data ingestion (batch/streaming), implement medallion/lakehouse designs, engineering transformations, and recommend governance, DevOps, and security best practices while working directly with clients.

The Information Management Engineer will oversee metadata management, master data models, integration pipelines, and data governance efforts, primarily utilizing Azure and GCP platforms.