We are looking for an experienced Data Engineer to join our team in the Metro Atlanta area. This role will focus on designing, developing, and optimizing data pipelines within a modern Azure cloud environment. The ideal candidate will have strong hands-on experience with Azure and Databricks, excellent problem-solving abilities, and the ability to work closely with Data Scientists and business stakeholders to deliver reliable, scalable data solutions. <br> Responsibilities: • Design, develop, maintain, and optimize scalable data pipelines and ETL/ELT processes. • Troubleshoot data pipelines that are missing SLAs by identifying bottlenecks and implementing solutions to improve performance and processing efficiency. • Work with large volumes of structured and unstructured data while maintaining strong data quality and reliability. • Develop and optimize data solutions using Python, SQL, PySpark, Azure, and Databricks. • Build and manage Databricks pipelines and workflows within a production environment. • Rework and improve existing data structures to support analytics, forecasting, and machine learning initiatives. • Partner closely with Data Scientists to develop and maintain data pipelines supporting predictive modeling and machine learning projects. • Analyze existing data environments and proactively identify opportunities to improve performance, reliability, and data quality. • Collaborate with technical teams and business stakeholders to understand requirements and translate complex data concepts into practical solutions. • Communicate effectively with customers and stakeholders, including those without a technical background. • Work independently in a fast-paced environment while adapting to changing priorities and project requirements. • Apply strong critical thinking and analytical skills to solve complex data engineering challenges. • Support data governance and data management best practices across the organization. • Utilize DevOps practices and tools, including Azure DevOps, to support efficient development and deployment processes. • Contribute to the development of modern data and analytics capabilities that support business intelligence, forecasting, and AI initiatives.

• At least 4 years of detail oriented experience in Data Engineering or a related field. • Strong hands-on experience with Microsoft Azure cloud environments and data engineering solutions. • Strong experience with Databricks, including Databricks Pipelines/Workflows and production data environments. • Proficiency in Python, SQL, and PySpark. • Experience designing, developing, and optimizing ETL/ELT data pipelines. • Strong understanding of data management, data quality, and data modeling principles. • Experience working with both structured and unstructured data. • Knowledge of the Apache Iceberg file format and modern data architecture concepts. • Demonstrated ability to troubleshoot data pipelines, identify performance bottlenecks, and optimize processes to meet SLAs. • Experience working with data pipelines supporting machine learning, predictive analytics, or data science initiatives is highly preferred. • Experience with Azure DevOps and Microsoft Fabric is a plus. • Strong analytical and critical-thinking skills with the ability to approach complex technical problems independently. • Strong communication and interpersonal skills, with the ability to translate technical data concepts for business and customer stakeholders. • Ability to work effectively in a fast-paced environment, adapt to changing priorities, and take initiative with minimal direction. • CPG, retail, or other high-volume data environment experience is a plus.

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