1. Manage databases on GCP (preferred) / AWS environments Drive cost optimization initiatives: Rightsizing, storage tuning, unused resource cleanup Ensure strong database security and encryption practices Own availability, performance, and reliability of MySQL and PostgreSQL production environments Lead P1/P2 incident management, deep troubleshooting, and RCA Drive improvements in MTTR, SLA adherence, and system resilience Design and maintain HA/DR architectures (replication, failover, clustering) 2. Migration & Modernization (High Priority Area) Lead MySQL → PostgreSQL migration programs Own end-to-end migration lifecycle: Schema conversion and compatibility validation Data migration strategy and execution Application query tuning and optimization Identify and mitigate risks around data types, indexing behavior, and query differences Ensure low-risk / minimal downtime migration execution 3. Performance Engineering & Observability Diagnose and resolve complex database performance issues Perform deep analysis on: Execution plans, locking, I/O bottlenecks, replication lag Implement observability using: SLI/SLO-based monitoring and alerting frameworks Leverage tools like: Grafana, Datadog, Splunk, SolarWinds DPA 4. Automation & Platform Engineering Drive automation-first mindset to eliminate manual toil Build and maintain frameworks using: GitHub Actions (GHA), Terraform, Ansible, Python/Bash Enable: Self-healing systems Automated failover, backups, patching, provisioning Standardize configurations and deployments across platforms 5. AI-Driven Operations Use AI-assisted tools to improve: Incident troubleshooting Query optimization Operational insights Identify use cases for AI-driven automation and observability enhancements Provide guidance and mentorship to L1/L2/L3 DBAs Review database designs, queries, and application architecture Drive best practices, SOP standardization, and knowledge sharing Act as a technical escalation point for complex issues 7. MySQL (primary large-scale production environments) PostgreSQL (EDB & Community) Deep understanding of: Replication, HA/DR, backup/restore strategies Schema transformation Query compatibility between engines Data migration tools and techniques Performance & Troubleshooting Query tuning and optimization Execution plan analysis High CPU / IO / locking issue resolution Automation & DevOps Terraform (IaC) GitHub Actions (CI/CD) Ansible / Python / Bash scripting Ability to build scalable automation frameworks Observability Grafana, Datadog, Splunk, DPA Strong understanding of: SLI/SLO and proactive alerting frameworks Cloud & Platform Exposure to: Exposure to AI tools (Copilot, Claude, AIOps platforms) Ability to apply AI to: Troubleshooting Automation Operational insights Bachelor's/master's in computer science or equivalent 9+ years of experience in DBA / DBRE roles
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