Position Summary
The Aurora PostgreSQL Database Administrator is responsible for secure, reliable, and high-performing database services and migrations from other database engines to Amazon Aurora PostgreSQL-Compatible Edition.
This role combines end-to-end migration delivery, advanced query and workload tuning, and replication and high-availability engineering. The DBA partners with application, DevOps, cloud, infrastructure, security, and service-management teams and supports production.
What You Will Do
Migration and Modernization
• Assess and plan: Inventory source schemas, code, dependencies, data volumes, service-level requirements, and compatibility gaps. Define migration sizing, effort, risks, and strategy.
• Design the approach: Select AWS DMS, DMS Schema Conversion and/or AWS SCT, native PostgreSQL utilities, logical replication, and custom SQL or scripts based on the source platform and downtime target.
• Convert and remediate: Transform schemas, data types, indexes, constraints, views, functions, procedures, triggers, jobs, extensions, and application SQL for Aurora PostgreSQL.
• Build migration pipelines: Configure and tune full-load and change-data-capture tasks, endpoints, replication resources, task settings, and monitoring for large tables, LOBs, throughput, and latency.
• Validate and cut over: Conduct test migrations, data reconciliation, performance and load testing, cutover rehearsals, rollback planning, production cutover, and post-migration stabilization.
• Document and coordinate: Maintain mapping decisions, issue logs, acceptance criteria, runbooks, and handoff documentation while partnering with application owners and technical stakeholders.
Performance and Tuning
• Baseline workloads: Measure database load, latency, throughput, waits, resource use, and growth with CloudWatch Database Insights, metrics, logs, Enhanced Monitoring, RDS events, and workload testing.
• Diagnose bottlenecks: Use EXPLAIN (ANALYZE, BUFFERS), pg_stat_activity, pg_stat_statements, aurora_stat_statements, relevant pg_stat views, lock and wait analysis, and database logs.
• Tune end to end: Optimize SQL, indexes, statistics, execution plans, parameter groups, memory, connections, temporary work, storage and I/O, and writer or reader sizing.
• Maintain PostgreSQL health: Manage VACUUM and ANALYZE, autovacuum, bloat, long-running transactions, transaction ID risk, WAL generation, and table or index growth.
• Prevent regressions: Use controlled testing, plan comparison, workload replay or load testing, and Aurora query plan management with apg_plan_mgmt where appropriate.
• Prove outcomes: Document measurable before-and-after results and recommend scalable, cost-conscious improvements to database configuration, SQL, and application design.
Replication, High Availability, and Recovery
• Aurora Replicas: Configure reader instances, reader endpoints, promotion tiers, failover behavior, read scaling, and replica health or lag monitoring.
• Logical replication: Implement and troubleshoot publications, subscriptions, replication slots, replica identity, WAL settings and retention, initial synchronization, conflicts, and lag.
• Migration replication: Support AWS DMS change data capture and monitor source and target latency, task health, recoverable errors, throughput, and data consistency through cutover.
• Cross-Region resilience: Support cross-Region replicas or Aurora Global Database where used. Test switchovers and failovers and validate application connectivity, RTO, and RPO.
• Recovery readiness: Own backup retention, snapshots, point-in-time recovery, restore testing, disaster-recovery runbooks, and recovery exercises.
Aurora Administration and Operations
• Administer Aurora PostgreSQL clusters, writer and reader instances, endpoints, parameter groups, extensions, backups, snapshots, maintenance, upgrades, capacity, and cost.
• Apply PostgreSQL roles and privileges, AWS IAM, TLS, AWS KMS, AWS Secrets Manager or CyberArk, VPC security groups, audit logging, and access reviews.
• Automate health checks, maintenance, deployments, reporting, and recovery tasks using Python, Bash or shell, SQL, AWS CLI/SDK, and infrastructure-as-code tools.
• Provide incident response, root-cause analysis, controlled production changes, operational documentation, monitoring, and rotational 24x7 on-call coverage as need it.
Required
• Three to five years of database administration or database engineering experience in a medium-to-large production environment.
• Strong hands-on administration of Amazon Aurora PostgreSQL-Compatible Edition, including cluster configuration, parameter groups, monitoring, backup and recovery, upgrades, security, and production support.
• Successful delivery of at least one end-to-end migration from a different database engine, such as Oracle, Sybase, SQL Server, MySQL/MariaDB, Db2, or a comparable platform, to Aurora PostgreSQL.
• Practical experience with AWS DMS full load and change data capture, schema and code conversion, migration troubleshooting, data validation, cutover, and rollback planning.
• Advanced PostgreSQL performance knowledge, including MVCC, locking, query planning, indexing, statistics, VACUUM and autovacuum, WAL, memory and connection management, and query-level diagnostics.
• Hands-on replication experience with Aurora Replicas and PostgreSQL logical replication, including lag monitoring, replication slots, WAL retention, failover, and recovery considerations.
• AWS experience with RDS/Aurora, CloudWatch Database Insights, IAM, KMS, Secrets Manager, VPC and security groups, snapshots, events, logs, and related networking.
• Scripting experience with Python, Bash or shell, and SQL, along with working knowledge of Linux/Unix and AWS CLI/SDK.
• Working knowledge of TCP/IP, DNS, ports, TLS, firewalls, and cloud network connectivity.
• Strong troubleshooting, documentation, communication, teamwork, and customer-service skills.
• Experience following production change, incident-management, security, and operational-control processes.
• Bachelor's degree in computer science, information systems, engineering, or a related discipline, or equivalent practical experience.
Preferred
• Deep source-platform knowledge in Sybase, SQL Server, MySQL/MariaDB, Db2, or another enterprise database engine used in heterogeneous migrations.
• Experience using DMS Schema Conversion or AWS SCT for complex database-code conversion, assessment reports, transformation rules, and remediation planning.
• Experience with Aurora Global Database, cross-Region disaster recovery, RDS Proxy, pglogical, advanced partitioning, or Aurora query plan management.
• Experience with infrastructure as code, Git, CI/CD, AWS CloudFormation, Terraform, and automated database deployment or validation pipelines.
• Familiarity with ServiceNow, Jira, Agile delivery, and structured incident, problem, and change management.
• Knowledge of regulated-environment controls such as HIPAA, SOX, or PCI DSS.
• Relevant AWS, PostgreSQL, or database-administration certification.
Work Expectations
• Support after-hours migrations, cutovers, maintenance, upgrades, recovery tests, and production incidents.
• Manage multiple priorities while maintaining disciplined change controls, clear documentation, and timely stakeholder communication.
Core Toolset at a Glance
Migration and Conversion
AWS DMS full load and CDC; DMS Schema Conversion and/or AWS SCT; premigration assessment; data validation; psql; pg_dump and pg_restore; SQL scripts; logical replication; CloudWatch task metrics and logs.
Performance and Diagnostics
CloudWatch Database Insights; CloudWatch metrics, logs, and alarms; Enhanced Monitoring; EXPLAIN (ANALYZE, BUFFERS); pg_stat_activity; pg_stat_statements; aurora_stat_statements; relevant pg_stat views; apg_plan_mgmt.
Replication, High Availability, and Recovery
Aurora Replicas; reader endpoints; promotion tiers; failover testing; logical replication; publications and subscriptions; replication slots; WAL monitoring; AWS DMS CDC; Aurora Global Database; snapshots and point-in-time recovery.
Automation, Security, and Service Management
Python; Bash or shell; SQL; AWS CLI/SDK; CloudFormation or Terraform; Git and CI/CD; IAM; KMS; Secrets Manager or CyberArk; TLS; ServiceNow or Jira; runbooks; change, incident, and problem management.