Director, Data Systems Software Engineering
DB Fleet Central is an OCI native cloud service for database fleet management and observability. It gives enterprise customers a way to monitor fleet health and availability, understand performance and capacity trends, manage databases, and investigate operational issues across cloud, hybrid, and multicloud environments. Its roadmap includes AI-assisted SQL and AWR insights, diagnostic assistance, fleet-wide anomaly and regression detection, and the AI Agent Observability platform.
As Director, you will set the engineering direction and lead the organization responsible for delivering these customer capabilities as reliable cloud services.
Responsibilities
Key Responsibilities
Data Systems Software Development
• Set engineering strategy for DB Fleet Central capabilities that help customers monitor fleet health and availability, understand performance and capacity, and manage database operations.
• Establish portfolio standards for data models, APIs, performance budgets, experimentation, and outcome measurement across service areas.
• Align multiple teams on roadmap priorities, dependencies, resourcing, quality standards, and customer outcomes.
• Lead and develop engineering managers and senior technical contributors; build the organization and technical leadership needed to deliver the service roadmap.
Software Development and Coding - Design, Testing, and Optimization
• Direct teams through the full lifecycle of cloud services and data systems: requirements, architecture, implementation, testing, release, and production operation.
• Set expectations for design and code reviews, automated functional and non-functional testing, performance profiling, API lifecycle, logging, metrics, and observability.
• Use product, adoption, performance, and service-health measures to steer delivery and continuous optimization.
Software Architecture - Software System Structural Design
• Set the architecture and technical direction for secure, highly available, scalable services that meet enterprise fleet needs.
• Lead the strategy and phased delivery of the AI Agent Observability platform as a core DB Fleet Central capability.
• Sponsor AI-assisted database performance and capacity insights, SQL and AWR analysis, diagnostic assistance, fleet-wide anomaly and regression detection, and root-cause analysis as these roadmap capabilities mature.
• Establish responsible AI standards for data protection, evaluation, traceability, monitoring, and human review of recommendations or actions.
• Guide architecture reviews and technology research across connected service areas.
Issue and Defect Collaboration - Software Products Support
• Direct cross-team response to complex customer issues and service incidents; ensure timely communication, prioritization, and durable resolution.
• Use customer feedback and support trends to shape product improvements and issue-handling practices.
• Partner with customer-facing leaders to maintain trust and align short-term mitigation with long-term fixes.
Practices and Standards Compliance - Security and Compliance
• Set and enforce service-wide standards for secure development, tenant isolation, privacy, data governance, and AI use.
• Ensure teams follow architecture, API, testing, and operational quality standards.
Development Operations - System Maintenance
• Own operational plans and outcomes for an always-on cloud service, including availability, capacity, performance, reliability, and customer SLOs and SLAs.
• Establish a sustainable on-call and escalation model; ensure teams are prepared for production support and incident leadership.
• Direct improvements to automation, deployment safety, monitoring, runbooks, patching, and root-cause follow-through.
Core Responsibilities
Planning and Execution: Oversee cross-team roadmaps, dependencies, resources, and milestones; adjust plans to maintain strategic outcomes.
Collaboration and Partnership: Align product, SRE, security, database, and infrastructure leaders around shared service goals.
Problem Solving: Guide teams through complex, ambiguous technical and operational problems and prevent recurrence.
Continuous Learning and Improvement: Build organizational expertise in database systems, cloud operations, and AI; use service and customer evidence to improve the roadmap.
Performance and Development: Coach managers and senior engineers, grow future leaders, and guide hiring and talent development.
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