Torchora
Back to Home

Key Responsibilities and Required Skills for Database Reliability Engineer

💰 $ - $

🎯 Role Definition

The Database Reliability Engineer (DRE) is responsible for ensuring the availability, performance, scalability, security, and cost-efficiency of an organization’s database systems and data platforms. A DRE designs and operates highly available database architectures (relational and NoSQL), leads incident response and postmortems for database outages, automates provisioning and deployment pipelines for databases, and partners with engineering and product teams to enable safe, performant data access at scale. The role blends classical database administration with SRE/DevOps practices — using infrastructure as code, observability, and automation to reduce toil while improving reliability, recoverability, and developer velocity.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Database Administrator (DBA) transitioning to SRE practices
  • Site Reliability Engineer (SRE) or DevOps Engineer with database focus
  • Data Engineer / Backend Engineer with operational responsibilities

Advancement To:

  • Senior Database Reliability Engineer
  • Lead/Principal DRE or Database Architect
  • Site Reliability Engineering Manager or Head of Data Platform
  • Cloud Database or Platform Engineering Lead

Lateral Moves:

  • Platform Engineer / Infrastructure Engineer
  • Data Platform Engineer
  • Performance Engineer / Query Optimization Specialist

Core Responsibilities

Primary Functions

  • Design, implement, and maintain highly available, fault-tolerant, and horizontally scalable database architectures (PostgreSQL, MySQL, Aurora, MariaDB, Cassandra, MongoDB, Redis, etc.) to meet production SLAs and SLOs across multiple regions and cloud providers.
  • Build and operate automated provisioning and lifecycle management for database clusters using Infrastructure as Code (Terraform, CloudFormation) and configuration management tools (Ansible, Salt), ensuring reproducible, documented deployments and repeatable rollbacks.
  • Lead database incident response and resolution for production outages, coordinate cross-functional on-call rotations, run postmortems, and drive remediation and systemic fixes to prevent recurrence.
  • Define and maintain database service-level indicators (SLIs), service-level objectives (SLOs), and error budgets; instrument metrics and alerting to proactively detect and remediate degradation in performance or availability.
  • Implement, test, and maintain robust backup, point-in-time recovery (PITR), disaster recovery (DR) strategies, and cross-region replication to ensure RTO and RPO targets are met and tested regularly.
  • Perform in-depth performance tuning at the system, query, and schema levels — include index strategies, query rewriting, execution plan analysis, partitioning, and memory/IO tuning to reduce latency and improve throughput.
  • Plan and execute database capacity planning, storage management, and cost optimization initiatives, including tiered storage, instance right-sizing, and reserved instance utilization across cloud platforms.
  • Design and execute complex data migrations and upgrades (on-prem → cloud, major version upgrades, cross-engine migrations) with minimal downtime using blue/green, canary, or rolling migration strategies.
  • Build and maintain observability tooling and dashboards (Prometheus, Grafana, Datadog, New Relic) to surface database health, slow queries, replication lag, resource bottlenecks, and long-term trends for capacity forecasting.
  • Automate schema migration workflows and manage database change control using tools like Flyway, Liquibase, Alembic, or custom migration tooling, with robust testing and safe rollbacks for production changes.
  • Manage replication topologies, clustering, sharding strategies, and failover automation (Patroni, Galera, MySQL Group Replication, Vitess) to ensure data consistency and high availability at scale.
  • Harden database security by implementing encryption at rest and in transit, role-based access control (RBAC), auditing, secure credential management (Vault), and network segmentation to meet compliance requirements (PCI, HIPAA, GDPR).
  • Develop and maintain internal database platform services (Database-as-a-Service) that enable application teams to provision, monitor, and operate databases with self-service interfaces and guardrails.
  • Integrate database lifecycle and quality checks into CI/CD pipelines to automate schema validation, migration testing, and pre-production performance tests before production rollouts.
  • Conduct proactive chaos testing, failover drills, and load/benchmark testing (sysbench, pgbench, JMeter) to validate resilience and to quantify behavior under stress and failure scenarios.
  • Mentor engineers and DBAs on best practices around transactional integrity, isolation levels, indexing, query patterns, and connection pool management to reduce production incidents and improve developer productivity.
  • Collaborate with platform, security, and application teams to design data models, indexing strategies, caching layers (Redis/Memcached), and query patterns that scale cost-effectively and meet product requirements.
  • Create and maintain runbooks, operational playbooks, and run-time documentation for common failure modes, maintenance procedures, and on-call steps to drive consistent, rapid incident recovery.
  • Evaluate and pilot new database technologies, plug-ins, and managed services (RDS, Aurora, Cloud Spanner, Bigtable, Cosmos DB) and make recommendations based on trade-offs for performance, cost, manageability, and feature fit.
  • Implement observability-driven remediation: enable automated remediations and safe rollback procedures for common incidents (auto-scaling, reconnect logic, query cancellations) while ensuring human oversight for risky operations.
  • Drive continuous improvement by analyzing incident trends, performing root cause analysis, and working cross-functionally to implement process, architecture, or tool changes that reduce mean time to recovery (MTTR) and mean time between failures (MTBF).
  • Ensure backup integrity, perform periodic restores in a staging environment, and validate data consistency, schema compatibility, and application-level behavior after restore operations.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis to help engineering and product teams understand production behavior and performance hotspots.
  • Contribute to the organization's data strategy and roadmap by recommending platform improvements, migration strategies, and operational standards.
  • Collaborate with business units to translate data needs into engineering requirements and prioritize reliability investments that align with product goals.
  • Participate in sprint planning and agile ceremonies within the data engineering and platform teams, helping to scope reliability and infrastructure work.
  • Maintain internal knowledge bases and runbooks; update runbooks after each incident and maintain a culture of blameless postmortems.
  • Provide training and onboarding for new engineers on database best practices, architecture, and operational procedures.
  • Participate in vendor evaluations and manage relationships with managed database providers and third-party monitoring/security vendors.
  • Support compliance audits by providing architecture diagrams, access logs, backup policies, and evidence of DR testing and security controls.

Required Skills & Competencies

Hard Skills (Technical)

  • Deep expertise with relational databases such as PostgreSQL and MySQL/MariaDB, including replication, partitioning, vacuuming/maintenance, query planner and execution plan analysis.
  • Strong experience with NoSQL and in-memory stores (Cassandra, MongoDB, DynamoDB, Redis) and understanding trade-offs for consistency, availability, and latency.
  • Proficiency in performance profiling and tuning: slow query analysis, index design, optimizer hints, connection pool tuning, and resource contention mitigation.
  • Hands-on experience with cloud managed database services (AWS RDS/Aurora, Google Cloud Spanner/Cloud SQL, Azure Database) and multi-region deployment patterns.
  • Infrastructure as Code and automation skills using Terraform, CloudFormation, Ansible, or similar, plus experience building repeatable deployment pipelines.
  • Observability and monitoring expertise: building dashboards, alerts, and tracing for databases using Prometheus, Grafana, Datadog, New Relic, ELK, or similar stacks.
  • Strong scripting and automation skills (Python, Go, Bash) to create tooling for maintenance, migrations, orchestration, and incident remediation.
  • Experience with containerization and orchestration (Docker, Kubernetes) for running stateful services and designing operator-based solutions for databases.
  • Proven ability with backup, PITR, snapshot management, and disaster recovery planning and execution across cloud and on-prem environments.
  • Familiarity with schema migration tools (Flyway, Liquibase), data migration strategies, and safe rollout patterns (canary, blue/green, transactional schema changes).
  • Security-focused skills: encryption (TLS, KMS), IAM integration, auditing, vulnerability management, and compliance controls for sensitive data stores.
  • Experience with load testing and benchmarking tools (sysbench, pgbench, JMeter) to validate scalability and guide capacity planning.
  • Understanding of networking, storage subsystems (EBS, SSDs), and their performance characteristics as they relate to database latency and throughput.
  • Knowledge of high-availability and clustering solutions (Patroni, Galera, Vitess, MySQL Group Replication) and automated failover mechanisms.

Soft Skills

  • Excellent problem-solving and troubleshooting skills with the ability to lead incident response under pressure and communicate status clearly to technical and non-technical stakeholders.
  • Strong written communication: create clear runbooks, postmortems, design documents, and onboarding material for cross-functional teams.
  • Collaborative mindset: work closely with application engineers, platform teams, security, and product owners to align reliability efforts with business priorities.
  • Proactive ownership and bias for automation: reduce manual toil, create self-service developer experiences, and continuously improve operational playbooks.
  • Mentoring and coaching experience: guide junior DBAs, DevOps, and engineers on best practices and operational maturity.
  • Prioritization and stakeholder management: balance feature delivery with technical debt, reliability work, and budgetary constraints.
  • Adaptability and continuous learning: keep up with database ecosystem changes, cloud offerings, and open source toolchains.
  • Customer-oriented perspective: translate platform reliability improvements into developer productivity and end-user impact.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field OR equivalent practical experience in database operations and platform engineering.

Preferred Education:

  • Master’s degree in Computer Science, Computer Engineering, Data Science, or related discipline preferred for senior and architect-level roles.
  • Professional certifications (e.g., AWS Database Specialty, Google Cloud Professional Data Engineer) are a plus.

Relevant Fields of Study:

  • Computer Science
  • Software Engineering
  • Information Systems
  • Data Engineering
  • Electrical or Computer Engineering
  • Cybersecurity / Information Assurance

Experience Requirements

Typical Experience Range: 3–8 years of hands-on experience operating production database systems, with demonstrated ownership of reliability, performance tuning, and automation.

Preferred:

  • 5+ years of experience in a role that blends database administration and site reliability engineering responsibilities.
  • Demonstrated experience with cloud database migrations, multi-region deployments, and architecting HA/DR solutions.
  • Proven track record of reducing MTTR, automating operational tasks, and improving database scalability and cost efficiency in production environments.
Explore More Careers