Database Engineer (Postgres)

TL;DR

Database Engineer (Postgres): Building and evolving the database layer for an AI-powered recruiting platform with an accent on schema design, advanced SQL, reporting datasets, and database governance. Focus on optimizing high-volume dashboard queries, supporting AI data consumers, and enforcing PII classification and retention policies across production systems.

Location: Fully remote from LATAM or the Philippines. Work schedule: 9:00 AM–6:00 PM PST.

Company

An AI-powered recruiting platform connects high-performing candidates with startups in the United States and Europe.

What you will do

• Extend and evolve PostgreSQL schemas across recruiting, candidate, and business operations data.
• Build SQL views, materialized views, and derived tables as standard interfaces for reporting and AI consumers.
• Optimize query performance through indexing, partitioning, execution-plan analysis, and query rewriting.
• Define and enforce column-level PII classification, data retention, and database governance policies.
• Collaborate with Engineering on webhook-driven ingestion and with AI Engineering on dataset consumption.
• Complete a schema audit, ship priority fixes, and improve p95 performance for key dashboard queries within the first 3–6 months.

Requirements

• 3+ years of experience working with production PostgreSQL databases.
• Advanced SQL skills, including window functions, CTEs, JSONB, EXPLAIN analysis, and performance-focused query rewriting.
• Experience with relational data modeling for OLTP and analytical use cases, including materialized views, indexing, and partitioning.
• Experience defining and enforcing PII, data-classification, and retention policies at the database level.
• Experience with Git-based schema migration workflows such as Flyway, Sqitch, or comparable tools, including pull-request review.
• Basic Python or comparable scripting skills and B2+ English required for technical documentation.

Nice to have

• Experience with Supabase, including RLS, authentication, Realtime, or Storage.
• Experience with dbt or SQLMesh for versioning SQL transformations.
• Experience exposing datasets to AI or ML consumers, such as feature datasets, embedding indexes, or evaluation sets.

Culture & Benefits

• Fully remote work from LATAM or the Philippines.
• Generous paid time off according to company policy.
• HMO coverage after three months for full-time employees based in the Philippines.
• Direct mentorship from international industry experts.
• Ongoing learning and development resources.
• Opportunities to connect with professionals worldwide.

Hiring process

• Application and screening.
• Skills assessment and Topgrading interview.
• Client interview, job offer, and client onboarding.