Data Engineer – Azure Databricks and Cloud Data Solutions (Safety)

Job Title: Data Engineer – Azure Databricks and Cloud Data Solutions (Safety) Why this role Southern Company’s Operations Data Analytics team supports the data foundations and integration capabilities needed to deliver reliable analytics and reporting across multiple organizations. This Data Engineer role will focus on Safety data and be responsible for creating data pipelines, curating source schemas, and supporting data product development in the Azure Databricks lakehouse platform. The role is important in creating secure, reusable, and high-performing data services that align with business needs, Technology Organization strategy, and enterprise standards. You will work directly with business and technology stakeholders to turn data requirements into practical solutions while improving performance, resource utilization, capacity planning, and application and data security. This role will support multiple business units and work in multiple lakehouse environments with data provisioned through Unity catalog, to create a unified foundation of safety and human performance data.

As part of this team, you will design, develop, implement, integrate, and support cloud and data solutions, with hands-on responsibility for data pipelines, data models, ETL processes, lakehouse capabilities, and data storage layers. You will partner with stakeholders, developers, and infrastructure teams to align solutions across technology platforms. The role also serves as a subject matter expert for data architecture and Databricks, supports operational issue resolution, and helps ensure that project documentation and change management requirements are met.

Design and develop robust data pipelines to ingest, store, and process data from multiple sources for analytics and reporting. Create and maintain logical and physical data models that organize data for efficient querying, analysis, and visualization. Build and maintain Extract, Transform, Load (ETL) processes that move data between systems while supporting data quality and consistency. Implement and support lakehouse solutions using medallion architecture, including data engineering pipelines and data storage layers. Optimize data lake storage, retrieval, performance, and resource utilization for analytical workloads. Develop dynamic, metadata-driven frameworks and scalable data ingestion patterns. Support streaming datasets and Databricks Delta Live Tables. Apply lakehouse performance-tuning techniques such as partitioning, aggregations, and materialized views. Architect, develop, implement, integrate, and support cloud technology solutions that meet business partner expectations for quality, cost, and timeliness. Work closely with developers and infrastructure teams to optimize application code, create reusable services, plan capacity, and protect application and data security. Become the team’s subject matter expert for data architecture and Databricks. Communicate effectively and promptly with customers, team members, and management, and build strong relationships with peers and business partners. Develop required project documentation, follow Change Management policies and procedures, and respond quickly and effectively to operational problems. Build a strong understanding of the company’s business challenges and goals and exhibit Our Values. What success looks like Reliable, efficient data pipelines that support analytics and reporting needs. Reusable and well-aligned solutions across on-premises and Azure technology platforms. Consistent, high-quality data movement through maintainable ETL and lakehouse processes. Optimized application code, cloud resources, performance, and capacity utilization. Secure data and application solutions supported by complete project documentation and disciplined change management. Strong working relationships and timely communication with business partners, technology teams, and management. Fast, effective resolution