Aurora PostgreSQL DBA / Database Migration Engineer

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. 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.

Our Client, an IT Services and Consultant company, is looking for an Aurora PostgreSQL DBA / Database Migration Engineer for their Remote location.
 
Responsibilities:

• 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.

 
Requirements:

• 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.

 
Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities