Database Architect
Summary
Designs, governs, and evolves an enterprise data platform spanning on-premises and cloud relational databases, owning data models, migrations, HA/DR, security, and performance tuning. Core technologies: Oracle, MySQL, and AWS RDS (including Aurora).
Project description
We are looking for an experienced Database Platform Automation Architect to establish and lead the automation foundation for a large, heterogeneous database estate: 12,000+ instances across Oracle, IBM DB2, MS SQL Server, PostgreSQL and NoSQL, running as PaaS, IaaS and on-premises. The estate is primarily on Azure and expanding to AWS and GCP. The role sits above day-to-day DBA operations, which are handled by a dedicated DBA team. It focuses on automating the lifecycle, configuration, compliance and visibility of the estate at scale, integrated with the client’s existing platform-engineering framework, Terraform modules, GitHub and ServiceNow. The architect will also apply AI and GenAI, such as AI agents for upgrade-readiness assessment and operational support, on top of this automation foundation.
Responsibilities
- Define and govern the automation architecture and roadmap for database platforms across Azure, AWS, GCP and on-premises. Design and deliver automation for the database lifecycle at estate level: provisioning, configuration, patching and upgrades, backup and restore, decommissioning. Build an estate-wide, near real-time inventory and configuration view (versions, extensions, sizing, networking, authentication) and detect drift against standards. Implement policy-as-code and compliance reporting for database platforms. Integrate automation with the existing platform-engineering framework (paved paths, reusable modules) and with ServiceNow (Service Catalog, change management). Lead the technical evolution of existing automation solutions and turn individual scripts into reusable, governed capabilities. Drive adoption of AI and GenAI for operations, for example AI agents for version-compatibility and upgrade-readiness assessment, with human-in-the-loop controls. Establish development standards, security controls, observability and code-review practices used by multiple teams. Collaborate with Database Engineering, Cloud, Platform Engineering, Security and Architecture teams, and mentor engineers.
SKILLS
Must have
- 8+ years in IT, including at least 3 years as an architect or technical lead in platform, cloud infrastructure or automation architecture. Proven, hands-on automation of database platforms at scale (hundreds or thousands of instances) across more than one engine (Oracle, IBM DB2, MS SQL Server, PostgreSQL), covering provisioning, configuration, patching and upgrades, and lifecycle management. Hands-on experience building estate-wide inventory, configuration visibility and compliance or drift reporting for cloud resources (for example Azure Resource Graph, cloud inventory APIs, CMDB integration). Policy-as-code and governance at organisation level (Azure Policy, OPA or Sentinel), including standards adopted by multiple teams. Terraform: personally authored reusable modules, state management and multi-environment deployments for managed and VM-based databases (Azure SQL, PostgreSQL Flexible Server, AWS RDS, GCP Cloud SQL). Ansible or equivalent configuration management for VM-based or on-premises database infrastructure. CI/CD with GitHub and GitHub Actions: reusable workflows, environments and approvals, secrets, self-hosted runners. ServiceNow integration: automating Service Catalog requests and change requests end to end (request → approval → pipeline → change record). Python, PowerShell and Bash scripting on Linux and Windows. Experience extending existing enterprise automation and platform-engineering frameworks (brownfield), not only building greenfield solutions. Practical, hands-on experience applying GenAI or AI agents to operational automation. Ability to clearly explain personal role, decisions and measurable outcomes on previous projects.
Nice to have
Microsoft AI stack: Azure OpenAI, Azure AI Foundry, Copilot Studio, Microsoft 365 Copilot extensibility AI agents that execute operational actions with human-in-the-loop approval, RBAC and audit trails Database version-compatibility and upgrade-readiness assessments at scale Automated Oracle or DB2 patching and upgrades, including HA setups (Oracle RAC or Data Guard, DB2 HADR) NoSQL databases on AWS or GCP Azure Arc or hybrid management of on-premises databases MCP (Model Context Protocol): building or integrating MCP servers RAG, vector and semantic search, AI orchestration frameworks Landing-zone design and multi-cloud governance (tagging, naming, guardrails) Security-by-design and threat modelling Certifications: Azure Solutions Architect Expert (AZ-305), HashiCorp Terraform Associate, Red Hat Ansible, AWS Solutions Architect, Azure AI Engineer (AI-102), TOGAF
Skills
- Agentic AI
- AI
- Ansible
- API
- Authentication
- Automation
- AWS
- Azure
- Bash
- CI/CD
- Cloud
- CMDB
- Db2
- GCP
- Generative AI
- GitHub
- GitHub Actions
- IaaS
- Linux
- MCP
- Microsoft Copilot
- Networking
- NoSQL
- Observability
- OpenAI
- Oracle
- PostgreSQL
- PowerShell
- Python
- RBAC
- RDS
- Semantic Search
- ServiceNow
- SQL
- SQL Server
- Terraform
- Threat Modeling