Data Engineer IV – Modern Enterprise / Lakehouse / AI-AssistedExperience Level: 5+ YearsWork Model: On-Prem + Cloud Hybrid EnvironmentsLocation- Atlanta, GAClient- Georgia PowerPosition OverviewThe Data Engineer IV is a modern enterprise data engineering professional responsible for building, optimizing, and maintaining scalable data platforms in a hybrid on-premises and cloud environment. This role supports enterprise analytics, reporting, and AI-driven initiatives using a Lakehouse architecture, with Databricks as the strategic future-state platform.The ideal candidate combines strong SQL and data modeling expertise with modern Spark-based technologies and familiarity with AI-assisted development tools.Core ResponsibilitiesEnterprise Data EngineeringDesign, build, and maintain batch and/or streaming data pipelinesDevelop and optimize ETL processes using SSIS or similar toolsWork with relational databases, data lakes, and NoSQL systemsNormalize and model data using: Star schema and dimensional modeling techniquesTransform raw data into curated, reusable datasetsLakehouse & Modern Data PlatformsDevelop and support solutions on Spark-based platformsWork with Databricks Lakehouse architecture (primary future-state platform)Support analytics and reporting via Power BIManage data orchestration workflows (e.g., Airflow or equivalent)Implement CI/CD and Git-based workflows for data pipelinesAI-Assisted & Modern Engineering PracticesLeverage AI tools or copilots to assist with: SQL development, pipeline generation, testing, documentationExplore automation or AI agents to streamline engineering workflowsTechnical Skills RequiredCore TechnologiesStrong SQL and data modeling experienceHands-on experience with: SQL Server, SSIS (or similar ETL tools), Power BIExperience with Spark-based platformsWorking knowledge of Databricks (preferred strategic platform)Data Engineering CompetenciesBatch and real-time pipeline developmentData quality and validation practicesRelational and NoSQL systemsOrchestration tools (Airflow or equivalent)CI/CD pipelinesGit-based version controlSoft Skills & Work Environment FitStrong written and verbal communication skillsComfortable collaborating with engineers and managers in electric utility and operations-heavy domainsAble to operate in regulated, production-critical enterprise environmentsAnalytical, detail-oriented, and solution-focusedExperience Requirements5+ years in data engineering or related software engineering rolesExperience in enterprise environments with hybrid on-prem and cloud systems