Senior PostgreSQL Database Reliability Engineer

Responsibilities:

• Production PostgreSQL infrastructure across the full lifecycle: architecture, deployment, replication, monitoring, performance tuning, backup/recovery, and capacity planning
• Streaming replication and high-availability configurations that meet the uptime expectations of a regulated financial exchange
• Query and system-level performance analysis—diagnosing slow queries, optimizing execution plans, tuning shared_buffers, work_mem, and autovacuum, not just reading pg_stat output but knowing what to do about it
• Backup and disaster recovery strategy using tools like Barman, including point-in-time recovery testing and validation
• Data architecture evolution: modernizing data warehouse and reporting infrastructure, building ETL pipelines, and designing data flows that scale with the business
• Data services across the organization: test data management, data obfuscation, data modeling, and supporting data needs for development, QA, and business teams
• Operational support including on-call rotation for after-hours production database emergencies

 

Skills, Knowledge and Expertise

Required

• 5+ years hands-on PostgreSQL administration in production environments—not just dev/test, not just managed RDS
• Deep understanding of PostgreSQL internals: WAL mechanics, MVCC, vacuum processing, the query planner and optimizer, connection handling, and lock management
• Proven experience with physical and logical replication: setup, monitoring, failover, and troubleshooting split-brain scenarios
• Strong SQL performance tuning skills: reading EXPLAIN ANALYZE output, identifying indexing strategies, understanding join algorithms, and resolving locking contention
• Solid Linux systems administration (we run Ubuntu)—comfortable with systemd, filesystem performance, memory management, and networking fundamentals
• Experience with backup/recovery tools (Barman, pgBackRest, or equivalent) and tested disaster recovery procedures
• Experience building and maintaining ETL pipelines and data transformation processes
• Bachelor’s degree in Computer Science, Information Systems, Mathematics, or a related field

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