Data Engineer 3 4P/444

Data Engineer III Experience: 5–10 Years Location: Birmingham, AL/ Atlanta, GA Contract- 1 Year Client- Alabama Power Position Overview We are seeking an experienced Data Engineer (Level 3) to build, optimize, and maintain scalable data pipelines and datasets that support business-critical analytics and applications. This role sits outside traditional IT and operates within the business technology/data domain—focused on ensuring clean, structured, and accessible data assets. The ideal candidate will have deep experience in data transformation, SQL optimization, Data Lakehouse architectures, and distributed processing systems. Proficiency in Databricks, Azure, Spark, Hive, and Airflow is required. Key Responsibilities Data Engineering & Pipeline Development Design, build, and maintain scalable and reliable data pipelines Combine raw data from multiple sources into clean, structured, machine-readable datasets Implement transformations using Spark, SQL, and ETL/ELT tools Normalize and model relational and distributed datasets to support analytics & applications Lakehouse & Cloud Engineering Develop and optimize data architectures in Databricks Lakehouse & Azure Manage ingestion pipelines across structured and unstructured data sources Apply data governance, quality, and lineage methodologies in cloud environments Data Modeling & Quality Create logical and physical data models to support business intelligence, ML, and analytics workloads Ensure data consistency, accuracy, completeness, and reusability Establish data quality frameworks, validation checks, and monitoring automation Experience 5–10 years in a Data Engineering role with hands‑on development Strong background in data manipulation & software engineering-oriented data practices Experience supporting enterprise-scale platforms Technical Skills Advanced SQL (query optimization, stored procedures, tuning) Databricks & Microsoft Azure Cloud (mandatory) Spark / Hive / Airflow Strong data modeling (star, snowflake, third-normal form) Experience building ETL/ELT pipelines in distributed environments #J-18808-Ljbffr