Lead Database Reliability Engineer Small Business positions focus on delivering results in their domain. This page aggregates open Lead Database Reliability Engineer Small Business roles and what employers typically expect.
## About the Role The Lead Database Reliability Engineer (DBRE) is a senior technical leader responsible for ensuring the reliability, scalability, performance, and operational excellence of the organization’s data platforms. This role blends **deep database expertise (DBA discipline)** with **Site Reliability Engineering (SRE) principles**, focusing on automation, observability, resiliency, and operational maturity. The DBRE partners closely with platform, application, and data teams to ensure database systems are highly available, cost-efficient, and production-ready at scale. ### **Database Reliability & Operations** - Own end-to-end reliability of critical database systems (availability, performance, durability) - Define and maintain SLIs/SLOs for database services - Lead incident response and root cause analysis for database-related outages - Design and implement failover, replication, and disaster recovery strategies ### **Automation & SRE Practices** - Automate database provisioning, scaling, backups, and recovery processes - Implement Infrastructure-as-Code (IaC) and GitOps approaches for database environments - Drive reduction of manual operational work through tooling and self-service capabilities - Establish reliability engineering practices (error budgets, postmortems, continuous improvement) ### **Observability & Performance** - Build and maintain database observability (metrics, logs, traces) - Proactively monitor system health and performance bottlenecks - Optimize query performance, indexing strategies, and resource utilization - Establish capacity planning and forecasting models ### **Platform & Architecture** - Partner with platform engineering to standardize database patterns and tooling - Support cloud-native database architectures (managed services, distributed systems) - Evaluate and recommend database technologies and storage solutions - Ensure systems are designed for resilience, scalability, and cost efficiency ### **Data Protection & Resilience** - Own backup strategies, validation, and restore testing - Lead disaster recovery planning and execution readiness - Ensure data integrity, consistency, and compliance with governance standards ### **Cross-Functional Collaboration** - Work with engineering teams to improve data access patterns and reliability - Partner with security and compliance teams on data protection requirements - Influence application design to align with database reliability best practices - Mentor engineers on database performance and operational excellence ### **Leadership & Influence** - Act as the technical lead for database reliability across teams - Define standards, best practices, and operating models for DBRE - Lead cross-team initiatives to improve reliability and reduce systemic risk - Mentor senior engineers and contribute to talent development ## **Success Profile (First 6–12 Months)** - Database SLIs/SLOs defined and actively managed - Automated backup, recovery, and failover processes in place - Improved observability across critical data platforms - Reduction in database-related incidents and MTTR - Standardized database reliability practices adopted across teams ## ## Required Qualifications - 8–12+ years in database engineering, SRE, or infrastructure engineering - Hands-on experience with production-grade relational and/or NoSQL databases (e.g., PostgreSQL, MySQL, SQL Server, DynamoDB, etc.) - Experience operating systems at scale in cloud environments (AWS, Azure, or GCP) - Proven ownership of high-availability, mission-critical systems - Strong knowledge of: - Database internals, replication, and recovery mechanisms - Performance tuning and optimization techniques - Distributed systems and fault-tolerant architectures - Experience with: - Observability tools (Datadog, Prometheus, Grafana, etc.) - Automation tools (Terraform, Ansible, CI/CD pipelines) - Containerization and orchestration (Docker, Kubernetes) - Familiarity with data lifecycle management and storage…