Data Engineer

Data Engineer SrLocation: Atlanta, GA (Onsite)Role OverviewThe Data Engineer is responsible for designing, building, and supporting scalable data platforms, data products, application integrations, and analytics solutions that enable business decision-making across Power Delivery. This role develops and maintains enterprise data pipelines, integrates operational systems with cloud-based lakehouse platforms, and supports both low-code and pro-code application development using Microsoft Power Platform, OutSystems, and Databricks. The successful candidate will partner with business stakeholders, data analysts, application developers, and technology teams to deliver trusted, governed, and reusable data assets.Key ResponsibilitiesDesign, build, and support enterprise data pipelines using ETL and ELT methodologies.Develop scalable ingestion frameworks for structured, semi-structured, and streaming data.Build and maintain Databricks notebooks, workflows, and data pipelines.Ingest data from source systems using Azure Data Factory, Kafka, CDC technologies, APIs, files, and database sources.Implement data quality checks, monitoring, and exception handling.Support Bronze, Silver, and Gold data architectures within the Databricks Lakehouse.Design and maintain Delta Lake tables and data products.Build and enhance business applications using Microsoft Power Apps, Power Automate, Power Platform, and OutSystems.Implement CI/CD practices using GitHub and Azure DevOps.Maintain documentation, lineage, and metadata for enterprise data assets.Required QualificationsEducation: Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related technical discipline.Experience: 3-7 years of experience in data engineering, analytics engineering, or software development, including building enterprise data pipelines and integrations, and working with cloud-based data platforms.Technical Skills:Data Engineering: ETL/ELT design, data ingestion frameworks, data pipeline orchestration, Data Warehousing concepts, Data Lake and Lakehouse architectures (Medallion architecture).Databricks: Databricks Workflows, PySpark, Spark SQL, Delta Lake, Unity Catalog, and Data Products.Cloud & Integration: Azure Data Factory, APIs, Kafka, CDC technologies, and SQL Server.Development: Python, SQL, GitHub, and Azure DevOps.Business Applications: Power Apps, Power Automate, Power Platform, and OutSystems.Preferred QualificationsUtility industry experience.Power Delivery domain knowledge.Experience supporting Transmission or Distribution Analytics.Real-time data streaming experience.Knowledge of AI/ML enablement on Databricks.Experience with Power BI integration and Direct Query architectures.Must be authorized to work in the US without sponsorship.