Lead Data Engineer

Job Summary We are seeking a Lead Data Engineer to provide hands-on technical leadership for a strategic enterprise data migration initiative supporting an Oracle Fusion Cloud implementation. This role is responsible for solution architecture, delivery planning, technical leadership, data modeling, and pipeline development while leading a team of data engineers to build scalable Databricks Lakehouse solutions. The ideal candidate will have deep expertise in Databricks, DBT, dimensional modeling, financial data domains, and Azure-based data engineering technologies. Key Responsibilities Lead the technical implementation, solution architecture, and delivery of enterprise data engineering initiatives. Provide technical leadership, mentoring, and coordination for a team of data engineers. Develop delivery plans, estimates, and work management strategies for project execution. Design, develop, and optimize Databricks Lakehouse solutions using medallion architecture. Lead pipeline development, DBT model development, conversion, and refactoring efforts. Design and maintain dimensional data models optimized for reporting and analytics. Optimize Gold-layer Delta tables for high-performance Power BI consumption. Develop Spark Declarative Pipelines using Lakeflow/DLT and Auto Loader. Implement and manage Unity Catalog for secure data governance. Collaborate with Business Intelligence and Quality Assurance teams to ensure data quality and successful solution delivery. Participate in technical design discussions and architecture reviews. Support migration of datasets, data products, and Power BI reports from legacy financial models to Oracle Fusion data models. Partner with QA teams to define testing criteria and validate data accuracy. Communicate technical blockers, project risks, sprint progress, and delivery timelines to project stakeholders. Identify project dependencies and proactively resolve technical challenges. Perform root cause analysis for data issues and implement effective solutions. Contribute to engineering standards, metadata-driven frameworks, and continuous improvement initiatives. Required Qualifications 12+ years of overall Data Engineering experience. 6+ years of professional experience working in the United States. 10+ years of hands-on Data Engineering experience. 5+ years of hands-on experience with Databricks. Strong expertise with Databricks Lakehouse architecture and principles. Hands-on experience with Unity Catalog. Experience developing Spark Declarative Pipelines using Lakeflow/DLT and Auto Loader. Strong pipeline development experience. Extensive experience with DBT model development, conversion, and refactoring. Advanced expertise in dimensional data modeling. Experience optimizing Delta tables for analytics and reporting. Strong SQL and PySpark development skills. Experience with medallion architecture. Experience with Azure DevOps CI/CD pipelines and Git. Exposure to Power BI and analytics consumption patterns. Experience with metadata-driven frameworks. Exposure to code generation and agentic engineering patterns. Experience optimizing data models for Power BI, including reducing downstream DAX complexity through upstream transformations. Familiarity with Oracle Fusion ERP data structures, BICC extraction patterns, or complex financial data domains. Strong analytical, problem-solving, and root cause analysis skills. Excellent verbal and written communication skills. Ability to collaborate effectively with cross-functional teams and technical stakeholders. Strong ownership, accountability, and ability to work independently. Ability to proactively identify risks, dependencies, and project blockers. Preferred Qualifications Experience leading enterprise Oracle Fusion Cloud migration initiatives. Experience leading teams of Data Engineers. Experience working with financial data, ERP systems, and enterprise reporting solutions. Experience supporting Business Intelligence and Quality Assurance teams throughout the software delivery lifecycle. Experience with Power BI semantic model optimization and refactoring. #J-18808-Ljbffr Compunnel, Inc.