> Markdown version of [/jobs/ext/4564716-data-engineer](https://www.wearedevelopers.com/jobs/ext/4564716-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Southern Company - **Location:** Atlanta, GA, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Microsoft Access, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Build Automation, Microsoft Azure, Big Data, Business Software, Databases, Continuous Integration, Information Engineering, Data Governance, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Systems, DevOps, Apache Hadoop, Apache Hive, Python (Programming Language), Machine Learning, Microsoft SQL Server, Microsoft Business Intelligence, OpenShift, Operational Databases, Performance Tuning, Power BI, SQL Databases, Unstructured Data, Informatica Powercenter, Delivery Pipeline, Apache Spark, Multi-Cloud, Parallel Computation, Containerization, Data Lakes, Information Technology, Oracle Golden Gate, Stream Processing, Azure Synapse Analytics, Software Version Control, Data Pipelines, Software Library, Docker, Databricks - **Published:** November 4, 2026 - **Apply:** https://dejobs.org/x/x/F3FD1353F1EB44F0A9E670660B679058/job/ ## About the Role * Bachelor's degree in Computer Science, Engineering, Machine Learning, or related field * 9+ years of experience in data engineering or related roles * Experience with batch and real-time data processing frameworks * Experience with big data technologies (e.g., Hadoop, HIVE, Spark) * Experience with AI/ML solutions in Python * 4+ years with on-prem tools (e.g., MSBI, Informatica, Oracle Golden Gate, SQL Server) * 2+ years with Microsoft Azure tools (e.g., Data Lake, Data Factory, Databricks, Synapse, Power BI) * Experience with containerization (e.g., Docker, OpenShift) Skills: * Proficiency in data modeling, access, storage, and quality tools * Familiarity with Agile, DevOps, CI/CD methodologies * Strong communication and collaboration skills * Ability to lead and mentor others * Familiarity with performance optimization and data governance * Proactive in sharing knowledge and best practices * Hands-on expertise with Databricks, SQL, Python, and Apache Spark. * Proficiency in data modeling for analytics and machine learning. ## Description The Electric Operations Technology Solutions (EOTS) Data Engineer is responsible for building, operationalizing, and maintaining data pipelines to support data, analytics, and AI use cases across hybrid and multi-cloud environments. The role involves translating data into consumable formats, supporting various data integration styles (e.g., virtualization, replication, streaming), and ensuring data reliability and scalability. The data engineer will lead standardization of data curation, data taxonomy and solution delivery across the Electric Operations Technology Solutions Organization for the Databricks and Azure environments. The position is on the Electric Operations Technology Solutions Leadership Team engaging in strategic delivery of business solutions supporting multiple business areas within Southern Company., Design and develop methods to process structured, semi-structured, and unstructured data using batch and real-time techniques * Develop release pipelines to automate build, version control, and deployment tasks * Build and maintain reusable templates, code libraries, and semantic models * Establish gatekeeping and guard rail processes for production data promotion * Collaborate with cross-functional teams including data, business, and technical stakeholders * Promote data reusability and modular data product delivery * Define and enforce data quality and integrity controls * Provide technical guidance to less experienced data engineers * Optimize performance using parallel processing and minimal data movement * Stay current with data technologies and share insights across the organization * Standardize, design, and develop Databricks applications, data integrations and automated business processes. * Integrate data from multiple systems, databases, APIs, and business applications. * Provide technical guidance, knowledge sharing, and support for business users and fellow data engineers.