Database Engineer

seRevel

New York (NY)

Remote

USD 120,000 - 170,000

Full time

14 days+
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Job summary

seRevel is an AI-native POC management platform built by Sales Engineers for Sales Engineers. The data lives in Postgres and you will own the database, including schema, performance, migrations, backups, and tenant isolation.

The team is small, early stage, and the data model is yours to shape. What you will do focuses on schema design for multi-tenant SaaS, enforcing isolation at the database layer, and running zero-downtime migrations while collaborating with Next.js and Node code.

Qualifications

  • Hands-on PostgreSQL in production: schema design, indexing, query tuning, and day-to-day operations.
  • Experience designing multi-tenant data models and explaining trade-offs.
  • Migrations on live systems and real restoration from backups.
  • Proficiency in TypeScript and Node.js to read and adjust queries.

Responsibilities

  • Own schema design for a multi-tenant SaaS: POCs, use cases, customer portals, synced integration data, and AI outputs.
  • Enforce tenant isolation at the database layer so no cross-workspace queries occur.
  • Design and run zero-downtime migrations alongside Next.js/Node code dependencies.
  • Tune performance for connector syncs and AI worker reads; optimize indexes and query plans.
  • Build and test backups, restores, and recovery processes.
  • Set up encryption at rest, TLS to the database, and least-privilege roles for services.
  • Plan for growth: partitioning, archiving, and capacity for increased data.

Skills

PostgreSQL
Schema design
Indexing
Query tuning
Tenant isolation
TypeScript
Node.js

Tools

Docker

Job description

seRevel is an AI-native POC management platform built by Sales Engineers for Sales Engineers, and all of it lives in Postgres: every POC, every use case, everything the connectors pull in from Salesforce, Gong, Jira and Slack, and everything the AI worker writes back. You will own that database. Schema, performance, migrations, backups, encryption, and the tenant isolation that keeps one company's data invisible to the next. Small team, early stage, and the data model is still yours to shape.

What you will do
  • Own schema design for a multi-tenant SaaS: POCs, use cases, customer portals, synced integration data, and the AI outputs built on top of them.
  • Enforce tenant isolation at the database layer so no query, job, or connector can cross workspace boundaries.
  • Design and run zero-downtime migrations alongside the engineers shipping the Next.js and Node code that depends on them.
  • Tune performance where it matters here: connector sync writes, the AI worker's reads, and the queries behind customer-facing pages. Indexes, query plans, connection pooling.
  • Build and test backup, restore, and recovery. Prove it works before anyone needs it.
  • Set up encryption at rest, TLS to the database, and least-privilege roles for every service that talks to it.
  • Plan for growth: partitioning, archiving, and capacity for what happens when the connectors sync ten times the data.
What we are looking for
  • Hands-on Postgres in production: schema design, indexing, query tuning, and day-to-day operations.
  • You have designed and run a multi-tenant data model and can explain the trade-offs you made.
  • You have shipped migrations on a live system without breaking it, and you have restored from a backup for real, not just configured one.
  • Comfortable enough in TypeScript and Node to read the code that queries the database and change it when needed.
  • You write clearly and work well async. We are remote-first.
Nice to have
  • Experience with Docker-based deployments and the infrastructure around a Postgres instance.
  • You have built or maintained connectors that sync third-party data (Salesforce, Jira, Slack, Gong, or similar) into a relational store.
  • You have been through a security review or compliance audit for B2B SaaS and know what gets asked about the database.
  • You have been an SE, or worked closely with sales engineering teams, and know what POC data looks like in practice.
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