It starts with you – a technical leader whos passionate about database systems and growing high-performing teams. You care about query performance, uptime, data durability, and operational excellence. Youll lead the Datastores team in operating, tuning, and scaling the database engines that serve the platform – from PostgreSQL to Elasticsearch, Redis to vector databases, across cloud and on-prem environments.
If you want to lead a team that keeps the database engines running for mission-critical AI systems, join mission – this role is for you.
:Responsibilities
Lead and grow the Datastores team – hiring, mentoring, and developing engineers while fostering a culture of operational excellence.
Own database reliability and availability – ensuring systems meet demanding SLAs for government and national-scale customers.
Drive performance tuning and optimization – query analysis, index strategies, configuration tuning, and resource optimization across all database engines.
Establish operational practices – backup/recovery procedures, disaster recovery, replication strategies, and failover automation.
Plan and execute capacity management – monitoring growth, forecasting needs, and scaling databases ahead of demand.
Lead incident response for database issues – troubleshooting, resolution, and post-incident improvements.
Enable new capabilities – evaluating, deploying, and operating new database technologies including vector databases for AI workloads.
Partner with Data Platform, Data Engineering, Engineering, and Security teams to align database operations with platform needs.
Define and uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate on schema evolution, partitioning, and safe replay/backfills.
Integrate with catalog and lineage systems – surfacing ownership, change history, and impact analysis for critical datasets and collections.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to prioritize performance, durability, and evolution of data stores across workloads.
If you want to lead a team that keeps the database engines running for mission-critical AI systems, join mission – this role is for you.
:Responsibilities
Lead and grow the Datastores team – hiring, mentoring, and developing engineers while fostering a culture of operational excellence.
Own database reliability and availability – ensuring systems meet demanding SLAs for government and national-scale customers.
Drive performance tuning and optimization – query analysis, index strategies, configuration tuning, and resource optimization across all database engines.
Establish operational practices – backup/recovery procedures, disaster recovery, replication strategies, and failover automation.
Plan and execute capacity management – monitoring growth, forecasting needs, and scaling databases ahead of demand.
Lead incident response for database issues – troubleshooting, resolution, and post-incident improvements.
Enable new capabilities – evaluating, deploying, and operating new database technologies including vector databases for AI workloads.
Partner with Data Platform, Data Engineering, Engineering, and Security teams to align database operations with platform needs.
Define and uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate on schema evolution, partitioning, and safe replay/backfills.
Integrate with catalog and lineage systems – surfacing ownership, change history, and impact analysis for critical datasets and collections.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to prioritize performance, durability, and evolution of data stores across workloads.
Requirements:
8+ years in database administration, database engineering, or storage infrastructure, with 2+ years leading teams or technical functions. Hands-on experience operating databases at scale.
Relational databases – PostgreSQL, MySQL; replication (streaming, logical), partitioning, connection pooling (PgBouncer), vacuum tuning, query plan analysis
Document & search engines – Elasticsearch, OpenSearch, MongoDB; cluster operations, shard management, index lifecycle, query optimization
Caching & key-value stores – Redis, DynamoDB, ScyllaDB; cluster modes, persistence options, eviction policies, memory optimization
Vector databases – Milvus, Qdrant, pgvector; index types (HNSW, IVF), similarity search tuning, embedding storage
Operations & reliability – Backup strategies, point-in-time recovery, disaster recovery, high availability configurations, failover testing
Performance tuning – Query optimization, index design, configuration tuning, resource profiling, slow query analysis
Monitoring & observability – Database metrics, alerting, capacity dashboards, performance trending
Cloud & managed services – AWS RDS, Aurora, ElastiCache, OpenSearch Service; managed vs self-hosted trade-offs
8+ years in database administration, database engineering, or storage infrastructure, with 2+ years leading teams or technical functions. Hands-on experience operating databases at scale.
Relational databases – PostgreSQL, MySQL; replication (streaming, logical), partitioning, connection pooling (PgBouncer), vacuum tuning, query plan analysis
Document & search engines – Elasticsearch, OpenSearch, MongoDB; cluster operations, shard management, index lifecycle, query optimization
Caching & key-value stores – Redis, DynamoDB, ScyllaDB; cluster modes, persistence options, eviction policies, memory optimization
Vector databases – Milvus, Qdrant, pgvector; index types (HNSW, IVF), similarity search tuning, embedding storage
Operations & reliability – Backup strategies, point-in-time recovery, disaster recovery, high availability configurations, failover testing
Performance tuning – Query optimization, index design, configuration tuning, resource profiling, slow query analysis
Monitoring & observability – Database metrics, alerting, capacity dashboards, performance trending
Cloud & managed services – AWS RDS, Aurora, ElastiCache, OpenSearch Service; managed vs self-hosted trade-offs
This position is open to all candidates.
