Senior Software Engineer, Database Engineer

TRM Labs; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Hidden Jobs is seeking a senior data platform engineer to own the relational database serving layer at petabyte scale, responsible for query performance, availability, and cost across production PostgreSQL clusters. This role blends deep database engineering with AI-assisted analysis to boost team leverage.

You will tune queries, design indexes, and build automation for routine tasks while managing CDC pipelines and migrations.

Qualifications

• 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.

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.

Skills

PostgreSQL production ops

SQL optimization

Explain plans

Window functions

Partitioning

CDC tools

Python

Go

AI tooling

pganalyze

PeerDB

Fivetran

Debezium

Datastream

Airbyte

AI copilots

Tools

pganalyze

PeerDB

Fivetran

Debezium

Datastream

Airbyte

Python

Go

Job description

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.