DBA Lead
1 week ago
We are looking for a DBA Lead to build and scale a world-class data platform supporting Oracle, PostgreSQL (including pgvector), Amazon Aurora/RDS, MongoDB, and DocumentDB. You will lead a hands-on team responsible for reliability, security, performance, and cost efficiency—enabling developers to provision, operate, and evolve databases through self-service, GitOps, and automation. Your work will establish the foundation that ensures data is secure-by-default, observable, and ready to power AI-enabled services across Unlimit.
$0 - $0 a month Must Have: 5–7+ years of experience in database engineering or administration, including at least 2+ years leading DBA teams. Expert in PostgreSQL, including physical/logical replication, partitioning, performance tuning, connection pooling (PgBouncer / RDS Proxy), vacuum strategy, and pgvector for embeddings. Expert in Oracle, including backup/restore, AWR/ASH diagnostics, Data Guard or managed equivalents, upgrade and patch strategies, and encryption. Proven hands-on experience with AWS data services in production: Aurora (Postgres/MySQL), RDS (Postgres/Oracle), DocumentDB, and MongoDB. Experience with vector databases and embeddings: storage design, ANN indexes, latency tuning, and maintenance strategies. Proven HA/DR design and PITR implementation experience. Strong background in security and governance: encryption at rest/in transit, RLS (Postgres) / VPD (Oracle), IAM roles and least-privilege models, Vault/KMS secrets management, and auditing. Infrastructure as Code for databases (Terraform modules for RDS/Aurora/DocumentDB/Mongo, plus VM-based Postgres/Oracle) with GitOps integration (Argo CD). Observability expertise: Performance Insights, CloudWatch, AWR, pganalyze/PMM, and the ability to define actionable dashboards and alerts.Nice to Have: Experience with multi-region or global topologies (Aurora Global, cross-region logical replication, Mongo/DocumentDB global clusters). Data migration and CDC tooling (AWS DMS, Debezium) and zero-downtime schema evolution. Workload isolation and routing strategies (read replicas, follower reads, connection pools, resource quotas). Cost and capacity optimization: instance and storage rightsizing, IOPS tuning, compression, and reserved instance planning. Experience integrating database observability signals into AIOps or ChatOps automations.
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