Responsibilities:Develop and implement data pipelines, utilizing ETL platforms and languages such as Databricks, Python, Spark, Scala, JavaScript/JSON, and PL-SQL.Design and maintain staging, fact, and dimension tables for relational databases.Extract, transform, and load (ETL) data from Oracle HCM and store it in AWS S3.Create and manage tables from extracted data and develop new scripts for ETL processes.Maintain and troubleshoot existing ETL pipelines, updating scripts as new data elements are introduced.Ensure data accuracy, integrity, and efficiency in processing large datasets.Collaborate with cross-functional teams to analyze data requirements and support business objectives.Work in a cloud-based environment using AWS and Databricks to manage and transform data.Optimize and automate database queries, ensuring scalability and performance.Minimum Requirements:3+ years of experience as a Data Engineer or Application Developer.Strong experience working with relational databases, including creating and managing staging, fact, and dimension tables.Proficiency in ETL processes and hands-on experience with Databricks, Python, Spark, Scala, JavaScript/JSON, and PL-SQL.Ability to design and maintain data pipelines to support analytics and reporting needs.B.A./BS or M.A./MSPreferred Qualifications:Experience working with cloud data structures, particularly AWS S3, Delta, and external tables.Familiarity with Oracle HCM or experience working with Oracle databases (a strong plus).Strong problem-solving skills and the ability to work independently with minimal oversight.Understanding of data transformation and how to optimize ETL scripts for efficiency.Experience with query optimization, performance tuning, and automation of data workflows.Security Clearance: Secret clearance required. recblid 38rqe841e4nb9tr5hegjvww3vlc3v7