Senior Database Administrator - Performance Tuning

Key Responsibilities :

- Performance Optimization & Query Tuning

- Tune query performance for PostgreSQL, EdgeDB, MongoDB Atlas, and Snowflake.

- Analyze execution plans, identify bottlenecks, and implement indexing & caching strategies.

- Work with engineering teams to optimize schema design for OLTP (Postgres/EdgeDB) and metadata storage (MongoDB).

- Database Architecture & Scalability

- Design multi-tenant scaling strategies for PostgreSQL and MongoDB Atlas (schema, sharding, partitioning).

- Implement high-availability, replication, and clustering configurations.

- Optimize Snowflake warehouse configurations for query speed and cost control.

- Operational Excellence

- Plan and execute zero-downtime database upgrades and schema migrations.

- Set up proactive monitoring, alerting, and anomaly detection across all database systems.

- Manage capacity planning for storage and compute resources across Postgres, MongoDB Atlas, and Snowflake.

- Storage & Cost Optimization

- Reduce storage costs via archiving, partitioning, compression, and lifecycle policies.

- Optimize Snowflake compute and storage usage with warehouse tuning and data pruning.

- Implement tiered storage strategies for cold vs. hot data.

- Security, Compliance & Governance

- Enforce encryption, access controls, and audit logging across all databases.

- Ensure compliance with GDPR, SOC 2, and other relevant regulations.

- Collaboration & Knowledge Sharing

- Partner with backend, platform, and data engineering teams to ensure efficient database usage.

- Provide training and documentation on query best practices and schema design.

Required :

- 7+ years DBA experience, with deep expertise in PostgreSQL and MongoDB Atlas.

- Strong understanding of multi-tenant architectures in production.

- Experience with Snowflake query optimization, warehouse tuning, and cost management.

- Proven success in executing zero-downtime upgrades and large-scale migrations.

- Strong skills in query optimization, indexing, partitioning, and sharding.

- Proficiency in scripting (Python, Bash, SQL) for automation.

- Hands-on experience with monitoring tools (pg_stat_statements, Atlas monitoring, Snowflake Resource Monitors, Prometheus, Grafana).

Nice To Have :

- Experience with EdgeDB or graph/relational hybrid databases.

- Familiarity with Kubernetes-based database deployments (StatefulSets, Operators).

- Background in distributed caching (Redis, Memcached).

Skills : DBA, PostgreSQL and MongoDB.