Senior Software Engineer, Database Engineer

Role overview

A senior engineering role on a data platform team that owns the relational database serving layer at petabyte scale. The position is end-to-end responsible for query performance, availability, and cost across production PostgreSQL clusters used by customer-facing APIs. It pairs deep database engineering with AI-assisted analysis and automation to raise the operational leverage of the entire team.

Responsibilities

- Maintain five-nines availability on customer-facing APIs through query tuning, index design, and schema optimization on large distributed Postgres deployments. - Use AI-assisted tooling to identify and ship storage and compute cost reductions, then validate changes in production. - Build agentic automation for routine database tasks such as connection pooler provisioning, disk scaling, and blue-green deployments. - Manage CDC pipelines and apply AI tooling to accelerate debugging of replication failures. - Drive migration of legacy workloads and prototype next-generation data stores. - Codify workflows into AI-native runbooks and internal tooling that teammates can reuse.

Requirements

- Five to eight years operating production PostgreSQL, including distributed variants such as Citus, Aurora, or AlloyDB. - Deep SQL optimization skills covering explain plans, CTEs, window functions, partitioning, and query planner behavior. - Hands-on experience with CDC tools such as PeerDB, Fivetran, Debezium, Datastream, or Airbyte. - Proficiency with database profiling tools like pganalyze or equivalent, including the use of LLMs to interpret findings. - Production automation experience in Python or Go, including agentic workflows for routine database operations. - Daily use of AI coding assistants such as Claude or Copilot to accelerate development, with sound judgment about when to trust the output.