Lead Principal Platform Software Engineer

Role Overview

Oracle AI Data Platform (AIDP) is a unified, enterprise-grade cloud service that brings together data management, governance, analytics, and generative AI development into a single platform. AIDP team is seeking an experienced Lead Principal Software Engineer to lead key initiatives that accelerate development and adoption of data platform capabilities.

In this role, you will drive the design, development, and integration of state-of-the-art technologies for data engineering that enable large scale AI enabled enterprise. You will provide technical leadership for our data connectivity frameworks and implement functionality such as zero-copy, Zero-ETL and data ingestion. You will architect and scale our enterprise data lineage functionality, using extensible open standards. You will build scalable, performant and secure frameworks to map end-to-end data flows - ensuring column-level visibility from source ingestion to downstream analytics.

You will collaborate with stakeholders across product, engineering, support and operations to influence the AI Data Platform’s roadmap and deliver differentiated value to enterprise customers and partners. You should be able to function well in a large geographically distributed team and have the hunger to drive for impactful results on a fast-paced environment.

Responsibilities

Required skills and experience

• Demonstrated technical leadership and architectural experience setting direction for complex systems, resolving ambiguous requirements, and driving initiatives across multiple engineering teams. Ability to balance scalability, reliability, security, performance, and delivery priorities.
• Strong hands-on software engineering experience with backend language such as Java or Python, with strong knowledge of API design, data modeling, and automated testing. Ability to diagnose complex failures across service and infrastructure boundaries.
• Strong understanding of concurrency, asynchronous processing, consistency, state management, retries, timeouts, idempotency, back-pressure, and recovery from partial failures, applied to large-scale or multi-tenant platform services.
• Data and integration experience building pipelines, connectors, or data platform components that integrate with heterogeneous external systems, including managing schema evolution and API and data contracts.
• Demonstrated hands-on use of Claude Code and/or Codex to deliver production software, including repository exploration, implementation planning, code generation, refactoring, debugging, test development, and code review.
• Ability to independently assess AI-generated designs, code, and tests; identify incorrect assumptions and missing coverage; and validate correctness, security, performance, and maintainability. Retains deep understanding and accountability for all delivered software.
• Experience owning services from design through deployment and operations, including observability, service-level objectives, incident response, root-cause analysis, capacity planning, and durable corrective actions.
• Ability to communicate trade-offs to engineering and product leaders, mentor senior engineers, and build reusable tools and practices that improve quality and delivery across teams.

Demonstrated technical leadership and architectural experience setting direction for complex systems, resolving ambiguous requirements, and driving initiatives across multiple engineering teams. Ability to balance scalability, reliability, security, performance, and delivery priorities.

Strong hands-on software engineering experience with backend language such as Java or Python, with strong knowledge of API design, data modeling, and automated testing. Ability to diagnose complex failures across service and infrastructure boundaries.

Strong understanding of concurrency, asynchronous processing, consistency, state management, retries, timeouts, idempotency, back-pressure, and recovery from partial failures, applied to large-scale or multi-tenant platform services.

Data and integration experience building pipelines, connectors, or data platform components that integrate with heterogeneous external systems, including managing schema evolution and API and data contracts.

Demonstrated hands-on use of Claude Code and/or Codex to deliver production software, including repository exploration, implementation planning, code generation, refactoring, debugging, test development, and code review.

Ability to independently assess AI-generated designs, code, and tests; identify incorrect assumptions and missing coverage; and validate correctness, security, performance, and maintainability. Retains deep understanding and accountability for all delivered software.

Experience owning services from design through deployment and operations, including observability, service-level objectives, incident response, root-cause analysis, capacity planning, and durable corrective actions.

Ability to communicate trade-offs to engineering and product leaders, mentor senior engineers, and build reusable tools and practices that improve quality and delivery across teams.

Preferred skills and experience

• Experience with data platform technologies such as Apache Spark, SQL processing engines, notebooks, or lakehouse architectures.
• Experience with orchestration or messaging platforms such as Apache Airflow, Temporal, Argo Workflows, Kafka, or comparable systems.
• Familiarity with OCI or other major cloud platforms, Kubernetes, infrastructure as code, CI/CD, and cloud identity and authorization.
• Experience designing extensible, connector-based architectures, with API versioning and backward compatibility for platform services used by many teams.
• Evidence of measurable engineering improvements through AI-assisted development, reusable agent workflows, and automated validation.

Experience with data platform technologies such as Apache Spark, SQL processing engines, notebooks, or lakehouse architectures.

Experience with orchestration or messaging platforms such as Apache Airflow, Temporal, Argo Workflows, Kafka, or comparable systems.

Familiarity with OCI or other major cloud platforms, Kubernetes, infrastructure as code, CI/CD, and cloud identity and authorization.

Experience designing extensible, connector-based architectures, with API versioning and backward compatibility for platform services used by many teams.

Evidence of measurable engineering improvements through AI-assisted development, reusable agent workflows, and automated validation.

Application Instructions

Apply directly on Oracle Careers at Lead Principal Platform Software Engineer↗.