Data Engineer IV

•Modern Enterprise / Lakehouse /

AI-Assisted Experience Level:

5+

Years Work Model:

On-Prem + Cloud Hybrid Environments Location

•Atlanta, GA/ Birmingham, AL. Client

•Georgia Power Position Overview The 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 Responsibilities Enterprise Data Engineering Design, build, and maintain batch and/or streaming data pipelines Develop and optimize ETL processes using SSIS or similar tools Work with relational databases, data lakes, and NoSQL systems Normalize and model data using: Star schema Dimensional modeling techniques Transform raw data into curated, reusable datasets Lakehouse & Modern Data Platforms Develop and support solutions on Spark-based platforms Work with Databricks Lakehouse architecture (primary future-state platform) Support analytics and reporting via Power BI Manage data orchestration workflows (e.g., Airflow or equivalent) Implement CI/CD and Git-based workflows for data pipelines AI-Assisted & Modern Engineering Practices Leverage AI tools or copilots to assist with: SQL development Pipeline generation Testing Documentation Explore automation or AI agents to streamline engineering workflows Technical Skills Required Core Technologies Strong SQL and data modeling experience Hands-on experience with: SQL Server SSIS (or similar ETL tools) Power BI Experience with Spark-based platforms Working knowledge of Databricks (preferred strategic platform) Data Engineering Competencies Batch and real-time pipeline development Data quality and validation practices Relational and NoSQL systems Orchestration tools (Airflow or equivalent) CI/CD pipelines Git-based version control Soft Skills & Work Environment Fit Strong written and verbal communication skills Comfortable collaborating with engineers and managers in: Electric utility Operations-heavy domains Able to operate in regulated, production-critical enterprise environments Analytical, detail-oriented, and solution-focused Experience Requirements 5+ years in data engineering or related software engineering roles Experience in enterprise environments with hybrid on-prem and cloud systems