Lead Principal Platform Software Engineer

Oracle•Redwood City, CA

About The Position

Oracle AI Data Platform (AIDP) is a unified, enterprise-grade cloud service bringing together data management, governance, analytics, and generative AI development. The AIDP team is seeking an experienced Lead Principal Software Engineer to lead initiatives that accelerate development and adoption of data platform capabilities. The role drives the design, development, and integration of data-engineering technologies for large-scale AI-enabled enterprises, including technical leadership for data connectivity frameworks and functionality such as zero-copy, Zero-ETL, and data ingestion. The engineer will architect and scale enterprise data lineage using extensible open standards, and build scalable, performant, and secure frameworks to map end-to-end data flows with column-level visibility from source ingestion through downstream analytics. The role collaborates with product, engineering, support, and operations stakeholders to influence the platform roadmap and deliver value to enterprise customers and partners. Success requires working effectively across a large, geographically distributed team and driving impactful results in a fast-paced environment.

Requirements

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 backend software engineering experience with a language such as Java or Python, including 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.
Ability to retain deep understanding of 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.

Nice To Haves

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.

Responsibilities

Lead key initiatives that accelerate development and adoption of data platform capabilities.
Drive the design, development, and integration of data-engineering technologies for large-scale AI-enabled enterprises.
Provide technical leadership for data connectivity frameworks and implement functionality such as zero-copy, Zero-ETL, and data ingestion.
Architect and scale enterprise data lineage functionality using extensible open standards.
Build scalable, performant, and secure frameworks to map end-to-end data flows, providing column-level visibility from source ingestion to downstream analytics.
Collaborate with product, engineering, support, and operations stakeholders to influence the AI Data Platform roadmap and deliver value to enterprise customers and partners.
Own services from design through deployment and operations, including observability, service-level objectives, incident response, root-cause analysis, capacity planning, and durable corrective actions.
Communicate trade-offs to engineering and product leaders, mentor senior engineers, and build reusable tools and practices that improve quality and delivery across teams.
Use AI coding tools to implement, refactor, debug, test, and review production software, while maintaining accountability for the delivered software.

Benefits

Medical, dental, and vision insurance, including expert medical opinion
Short-term and long-term disability
Life insurance and AD&D
Supplemental life insurance for employees, spouses, and children
Health care and dependent care flexible spending accounts
Pre-tax commuter and parking benefits
401(k) Savings and Investment Plan with company match
Paid time off, including flexible vacation for eligible salaried employees or accrued vacation for other eligible employees
11 paid holidays
Paid sick leave
Paid parental leave
Adoption assistance
Employee Stock Purchase Plan
Financial planning and group legal benefits
Voluntary auto, homeowner, and pet insurance