10 days ago
Base Salary
$114k - $306k/yr
Responsibilities
- Lead architecture and technical direction for complex data platform systems across multiple engineering teams.
- Design and develop data connectivity frameworks, zero-copy and zero-ETL functionality, and data ingestion capabilities.
- Architect and scale enterprise data lineage with column-level visibility across ingestion and downstream analytics.
- Build scalable, performant, secure, and multi-tenant platform services supporting heterogeneous external systems.
- Own services from design through deployment and operations, including observability, service-level objectives, incident response, root-cause analysis, and capacity planning.
- Use Claude Code and/or Codex for repository exploration, implementation, refactoring, debugging, testing, and code review.
- Assess AI-generated designs, code, and tests for correctness, security, performance, and maintainability.
- Collaborate with product, engineering, support, and operations stakeholders to influence roadmap and deliver platform value.
- Mentor senior engineers and create reusable tools and practices that improve engineering quality and delivery.
Requirements
- Strong technical leadership and architectural experience setting direction for complex systems and resolving ambiguous requirements.
- Strong hands-on backend software engineering experience with Java or Python, including API design, data modeling, and automated testing.
- Strong understanding of concurrency, asynchronous processing, consistency, state management, retries, timeouts, idempotency, back-pressure, and partial-failure recovery.
- Experience building data pipelines, connectors, or data platform components integrating heterogeneous external systems, including schema evolution and API and data contracts.
- Demonstrated production use of Claude Code and/or Codex for software development.
- Ability to independently validate AI-generated designs, code, and tests and retain accountability for delivered software.
- Experience owning services through deployment and operations, including observability, service-level objectives, incident response, root-cause analysis, capacity planning, and corrective actions.
- Ability to communicate trade-offs to engineering and product leaders, mentor senior engineers, and improve practices across teams.
- Preferred experience with Apache Spark, SQL processing engines, notebooks, or lakehouse architectures.
- Preferred experience with Apache Airflow, Temporal, Argo Workflows, Kafka, or comparable orchestration and messaging systems.
- Preferred familiarity with OCI or other major cloud platforms, Kubernetes, infrastructure as code, CI/CD, and cloud identity and authorization.
- Preferred experience designing connector-based architectures with API versioning and backward compatibility.
- Preferred evidence of measurable engineering improvements through AI-assisted development, reusable agent workflows, and automated validation.
Benefits
- US base salary range is $113,600 to $306,400 per year, with possible bonus, equity, and compensation deferral.
- Benefits include medical, dental, vision, disability, life insurance, flexible spending accounts, commuter and parking benefits, 401(k) matching, paid vacation, paid holidays, paid sick leave, parental leave, adoption assistance, employee stock purchase, financial planning, group legal, and voluntary insurance benefits.
- US-based employees must complete identity verification involving collection and processing of biometric information, subject to legally permitted accommodations.
Tech Stack
Categories
BackendData Engineering
About Oracle
Oracle builds database technology, enterprise applications, and Oracle Cloud Infrastructure for companies and governments. Its business spans cloud subscriptions, software licenses, and support services across ERP, HCM, CX, and industry suites, plus NetSuite. Founded in 1977 and headquartered in Austin, Texas, Oracle is a public company traded on the NYSE and serves global customers migrating and running critical workloads in its cloud.