לוח משרות דרושים מומחה Storage משרה מלאה

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.

It starts with you - an engineer driven to operate database systems at the highest level of reliability and performance. You care about query latency, uptime, data durability, and getting paged as little as possible. Youll operate, tune, and scale 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 run the databases that power mission-critical AI at national scale, join Dreams mission - this role is for you.
The Dream-Maker Responsibilities
Operate and maintain database systems - PostgreSQL, Elasticsearch, Redis, MongoDB, vector databases, and others across cloud and on-prem.
Own database reliability - high availability configurations, replication, failover automation, and SLA adherence.
Drive performance tuning - query optimization, index design, configuration tuning, and resource profiling to meet latency and throughput targets.
Execute operational procedures - backup/recovery, disaster recovery testing, upgrades, migrations, and capacity scaling.
Lead incident response for database issues - troubleshooting production problems, root cause analysis, and implementing preventive measures.
Build monitoring and alerting - dashboards, metrics collection, slow query analysis, and proactive capacity alerts.
Enable new capabilities - deploying and tuning vector databases for AI workloads, evaluating new database technologies.
Collaborate with Data Platform, Data Engineering, Engineering, and Security teams on database operations and best practices.
Uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate safe schema evolution, partitioning, and replay/backfill practices.
Expose catalog and lineage signals - ownership, change history, and impact analysis - to improve trust and safe consumption for downstream users.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to balance performance, durability, and evolution across workloads.