Technical Leadership:
Own the technical vision, architecture, and roadmap for the DBaaS platform. Translate strategic initiatives into architecture decisions, technical requirements, and an actionable delivery plan.
Lead design and architecture reviews, and maintain design documents and platform standards.
Break down, estimate, and prioritize work; manage dependencies and risks; and track delivery against commitments using Agile practices.
Serve as the technical escalation point for complex production issues, lead root-cause analysis, and drive durable engineering fixes.
Set and enforce engineering quality standards: code review, automated testing, CI/CD, security scanning, and release governance.
Champion AI-augmented engineering: drive adoption of AI coding assistants and agentic tools, and define team practices and quality gates aligned with enterprise AI governance, security, and data-handling policies.
Measure the impact of AI tooling on delivery speed, quality, and risk, and identify opportunities to apply AI within the DBaaS platform itself.
Mentor and grow engineers, delegate ownership, and reduce concentration of knowledge in critical platform areas.
Partner with application engineering, DBA, infrastructure, cloud, and security teams to align requirements, interfaces, and delivery timelines, and guide platform adoption.
Job Responsibilities:
Remain hands-on: design, code, test, and review backend services, automation operations, and platform tooling in Python using object-oriented design principles, API-driven workflows, and reusable engineering patterns.
Evolve the order execution framework for scalable asynchronous processing, multi-stage workflows, bulk execution, and idempotent retries.
Guide automation for the full database lifecycle, from provisioning and patching to backup, recovery, and decommissioning, across on-premises and cloud environments.
Drive the automation strategy for database services across hybrid and multi-cloud platforms.
Define Terraform standards for reusable modules, state management, versioning, and integration with the DBaaS orchestration layer.
Design and govern integrations with enterprise platforms such as AWX/Ansible, CMDB, credential vaults, and entitlement systems.
Define API design, versioning, and backward-compatibility standards, and own the lifecycle of APIs, actions, and workflows, including deprecation and technical-debt reduction.
Design data models and automation patterns that work consistently across multiple database platforms, such as Oracle, SQL Server, PostgreSQL, and MongoDB.
Establish observability standards and service-level objectives, and use them to prioritize reliability and capacity improvements.
Ensure solutions meet enterprise requirements for security, entitlement, auditability, compliance, and change control.
Core skills
10+ years of software engineering experience, including 3+ years in a technical lead or senior lead role guiding a development team.
Proven track record of designing, building, and operating production-grade automation platforms or infrastructure tooling at enterprise scale, preferably for database or infrastructure lifecycle management.
Expert-level Python skills, including object-oriented design, packaging, testing (pytest), asynchronous and concurrent processing, and code quality tooling. Strong Shell scripting skills.
Strong experience with backend service development, RESTful API design, integration patterns, and distributed or queue/worker-based architectures.
Experience with Python web frameworks such as Django and Flask, and with ORMs and relational schema design.
Proven automation-first mindset with deep hands-on experience automating infrastructure and database provisioning using Terraform, including authoring and governing reusable Terraform modules.
Working knowledge of the mechanisms used to automate multiple database platforms, including direct database integration, API-based orchestration, and Ansible/AWX-driven automation.
Strong hands-on experience with AI coding assistants and agentic development tools, including prompt and context engineering and integrating AI into engineering workflows (for example, MCP-based tool integrations and AI-assisted code review in CI/CD), with the judgment to review, validate, and own AI-generated output.
Experience with Git-based workflows, CI/CD pipelines, Ansible/AWX, containerization, and Agile engineering practices.
Strong troubleshooting skills for diagnosing automation failures across application, database, operating system, infrastructure, and cloud layers.
Excellent written and verbal communication skills, with the ability to present architecture and trade-offs to engineers and senior stakeholders.
Preferred experience
Experience automating Oracle Cloud Infrastructure (OCI) database services, such as Exadata, compartments, networking, and vault.
Experience automating Microsoft Azure services supporting Oracle workloads, such as Oracle Database[redacted], SQL MI, networking, and backup and restore.
Familiarity with highly available and resilient database architectures (e.g., RAC, Data Guard, disaster recovery).
Familiarity with Oracle security features (e.g., TDE, data masking, auditing).
Ways of working
Leads by example: combines hands-on engineering with clear technical direction and accountability for team outcomes.
Balances strategic platform evolution with critical operational priorities, making pragmatic trade-offs and communicating them clearly.
Models effective, responsible use of AI and coaches the team to adopt it.
Builds consensus across engineering, DBA, infrastructure, security, and support teams, and drives decisions to closure.
Demonstrated ability to mentor engineers, grow technical leaders, share knowledge, and establish platform best practices.
Flexible during critical delivery windows and committed to continuous improvement, resiliency, and automation-first engineering.
Note on standards
The Tech Lead is accountable for ensuring the team aligns to enterprise engineering standards for API design, versioning, service integration, security, and operational supportability to ensure predictability, governance, backward compatibility, and sustainable platform growth across database automation solutions.
