Gather AI - Staff Database Engineer
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Requirements
• 6–8+ years operating production relational databases • Deep PostgreSQL expertise (replication, indexing, tuning, upgrades) • Expert-level SQL and execution plan analysis • Strong UNIX systems knowledge • Strong proficiency in at least one programming language (Python preferred) • Proficiency in shell scripting (Bash or similar) • Experience troubleshooting at OS + database boundary • Experience supporting SLA-backed production systems • Multi-tenant database design experience • Backup, HA, and disaster recovery implementation experience • Experience in ISO/SOC2 or compliance-aware environments • Cloud-native database operations (Azure preferred) • Experience designing multi-region read/write strategies • MongoDB deep performance tuning • Data lifecycle automation (archiving, pruning, tiering) • CDC pipelines or event streaming familiarity • Experience supporting AI/ML workloads • Experience formalizing database governance practices • Architect and optimize PostgreSQL and MongoDB to support LLM-generated and dynamically composed queries without compromising transactional performance or SLA commitments. • LLM-generated and dynamically composed queries • Design isolation and workload-segmentation strategies (replicas, caching, materialized views, routing) to protect production systems from exploratory, reporting, or AI-driven query impact. • Own measurable improvements in multi-faceted reporting and data retrieval latency across operational, analytical, and AI-powered use cases.
Responsibilities
• Lead the design, optimization, and scaling of relational and distributed databases to meet uptime, performance, and latency goals • Define and implement replication, multi-region read/write strategies, backup/HA, and disaster recovery • Establish governance, compliance (ISO/SOC2), and operational standards for data infrastructure • Drive database performance tuning, capacity planning, and lifecycle automation • Collaborate with engineering and infrastructure teams to ensure data systems meet SLAs and support AI/ML workloads • Provide architectural leadership on PostgreSQL and MongoDB systems and scaling approaches
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