Top Data Engineer Jobs in Atlanta, GA

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.

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.

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.

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.

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.

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.

Maintain data integrity and quality through advanced testing and validation of ETL pipelines. Analyze complex data issues, build solutions, mentor junior staff, engage with clients, and support continuous improvement across data management, governance, and pipeline orchestration.

As a Data Engineer I, you will design, build, and maintain data systems and pipelines for analytics, requiring technical skills in programming and data architecture.

Design, build, and maintain scalable ETL/ELT pipelines and data platforms using PySpark and Azure Databricks. Parse and process structured and unstructured data, support platform scaling/monitoring/operation, and collaborate with multidisciplinary teams to deliver analytics that inform clinical and public health decision-making.

Design, build, and maintain scalable ETL/ELT pipelines and data platforms (Azure Databricks/PySpark) to process structured and unstructured data. Lead cross-functional teams, support analytical exploration, convert diverse data into usable formats, and communicate technical findings to clinical and public health stakeholders while meeting government vetting and Public Trust requirements.

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

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.

Join Cox Automotive as an entry-level Data Engineer to build, maintain, and improve cloud-based data pipelines and assets. Work with SQL and Python, use AI-powered coding assistants, support data quality and integrity, participate in Agile development, and gain exposure to Snowflake and AWS AI services.

Build and maintain batch and streaming data pipelines, transform and document datasets, implement data quality and observability, support ML training datasets, and collaborate with product and analytics partners to deliver reliable, production-ready data products that enable reporting and machine learning use cases.

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

The role involves designing, building, and maintaining ERP data pipelines, ensuring their reliability and supporting data integration initiatives. Responsibilities include troubleshooting, implementing SDLC best practices, and collaborating with stakeholders to optimize data-related outcomes.

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.

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

The Data Engineer will design, build, and maintain data pipelines and ETL/ELT workflows, optimizing data processes across various platforms while supporting analytics and machine learning use cases.

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.

The Data Engineer is responsible for developing data infrastructure, building data pipelines, managing data quality, and integrating analytics tools to support design and project operations.