Senior Principal Data Engineer, CSS SaaS and Apps Delivery - Analytics

Oracle is seeking a highly skilled Data Engineer to support enterprise customers adopting Oracle AI Data Platform. In this role, you will design, implement, support, and operationalize advanced, cloud-native data architectures that enable high-performance analytics and machine learning at scale.

Responsibilities:

• Design, implement, and support end-to-end data ingestion, transformation, and orchestration pipelines leveraging:
• OCI Data Lakehouse Services: Object Storage, Lakehouse, Autonomous Data Warehouse
• Real-Time Data Movement: Oracle GoldenGate, OCI Streaming, Kafka-compatible services
• Data Integration & Orchestration: OCI Data Integration, Data Flow (Apache Spark), Data Catalog, OCI Data Science integration
• Implement and support distributed data processing patterns including ELT, event-driven streaming, and micro-batch frameworks
• Apply advanced performance engineering techniques for partitioning, indexing, caching, and adaptive query optimization
• Design secure and compliant data environments integrating IAM, Vault, KMS, VCN security, and data governance standards
• Enable model-ready datasets using feature engineering pipelines, metadata standardization, and lineage automation
• Perform troubleshooting and root cause analysis on pipeline failures, optimize pipeline SLAs, and ensure observability via OCI Logging & Monitoring
• Collaborate with customer architects and Oracle product teams to accelerate adoption of AI-powered data capabilities
• Understands how to handle large blobs of time series data
• Can write batch process code in Python, understands dataframes

Requirements:

• Design, implement, and support end-to-end data ingestion, transformation, and orchestration pipelines leveraging OCI Data Lakehouse Services: Object Storage, Lakehouse, Autonomous Data Warehouse
• Implement and support distributed data processing patterns including ELT, event-driven streaming, and micro-batch frameworks
• Apply advanced performance engineering techniques for partitioning, indexing, caching, and adaptive query optimization
• Design secure and compliant data environments integrating IAM, Vault, KMS, VCN security, and data governance standards
• Enable model-ready datasets using feature engineering pipelines, metadata standardization, and lineage automation
• Perform troubleshooting and root cause analysis on pipeline failures, optimize pipeline SLAs, and ensure observability via OCI Logging & Monitoring
• Collaborate with customer architects and Oracle product teams to accelerate adoption of AI-powered data capabilities
• Understands how to handle large blobs of time series data
• Can write batch process code in Python, understands dataframes