Data Engineer with Oracle Fusion Data Intelligence, Oracle Utilities Data Intelligence, and AIDP

Remote: Data Engineer with Oracle Fusion Data Intelligence, Oracle Utilities Data Intelligence, and AIDP \_ New Orleans, Louisiana. Work Arrangement: Can be 100% Remote Candidates must be able to participate in video interviews. There will be 2 video interviews. Work Authorization: Candidates can be anywhere from EAD through U.S. Citizen. No H-1B candidates unless they are currently on your payroll and can be transferred with no delays or issues. WORKING RELATIONSHIPS The Data Engineer works closely with the Data Architect, Data Analysts, application owners, database administrators, information security and governance partners, Oracle and implementation vendors, business subject-matter experts, and the Data & Analytics Manager. The role translates business and architectural requirements into dependable data pipelines and supports timely resolution of production issues so decision-makers can rely on accurate, secure, and well-documented data. Preferred Experience • Direct experience with Oracle Fusion Data Intelligence (FDI) and/or Oracle Utilities Data Intelligence (OUDI) is preferred but not required. • Experience with Oracle Autonomous Database or Autonomous Data Warehouse, Oracle Analytics, Oracle Goldengate, Oracle Data Integrator, or comparable Oracle integration and analytics technologies. • Experience in utilities, energy, or another regulated industry, including work with financial, customer, usage, asset, or operational data. • Knowledge of version control and CI/CD practices for data solutions. • Relevant Oracle, database, cloud, or data-engineering certification is a plus. MINIMUM REQUIREMENTS Minimum education required of the position • Bachelor’s degree in computer science, Information Systems, Data Engineering, or related field. Minimum experience required of the position • 3-6 years of professional experience in data engineering, ETL/ELT development, database development, or a similar role. • Demonstrated experience building and supporting data solutions on enterprise relational or analytical platforms. Oracle database experience is valued; candidates with strong transferable database fundamentals must be able to learn unfamiliar Oracle platforms quickly and methodically. • Strong proficiency in SQL and working proficiency in Python for data transformation, automation, testing, and troubleshooting. • Experience with ETL/ELT, orchestration, scheduling, monitoring, and incremental-loading or CDC patterns, including error handling, restorability, and reconciliation. • Solid understanding of data modeling, large-scale data handling, data quality, performance optimization, security and governance, documentation, and production support; able to troubleshoot systematically across source, pipeline, database, and analytical layers. Preferred • Direct experience with Oracle Fusion Data Intelligence (FDI) and/or Oracle Utilities Data Intelligence (OUDI) is preferred, not required. • Experience with Oracle Autonomous Database or Autonomous Data Warehouse, Oracle Analytics, Oracle Goldengate, Oracle Data Integrator, or comparable Oracle integration and analytics technologies. • Experience in utilities, energy, or another regulated industry, including work with financial, customer, usage, asset, or operational data. • Knowledge of version control and CI/CD practices for data solutions, or a relevant Oracle, database, cloud, or data-engineering certification. COMPETENCIES • Structured analytical and problem-solving mindset with strong attention to detail, data integrity, and business impact. • Learning agility and curiosity when working with unfamiliar Oracle products, schemas, metadata, and vendor-managed components; validates assumptions through documentation, data, and small test cases. • Clear communication with technical and business stakeholders, including concise incident updates, documentation, and explanation of trade-offs. • Collaborative and team-oriented approach across data, application, infrastructure, security, governance, vendor, and business teams. • Ownership and accountability for reliable data operations, with sound judgment under pressure and a commitment to continuous improvement.