Manage and scale PostgreSQL and Supabase databases with hybrid search capabilities, focusing on schema design, data modeling, and performance optimization as data volume grows indefinitely.
Implement end-to-end data quality processes including validation checks for third-party and vendor data, deduplication, entity resolution, data provenance tracking, and continuous monitoring.
Build and maintain a communications data layer that securely stores raw emails and call transcripts, links them to relevant people and organizations, and enables efficient search.
Develop scalable ingestion and enrichment pipelines for funding data, market news, and contact/company intelligence, optimized for cost-efficiency and data freshness.
Design and evolve a knowledge graph within Postgres using node and edge tables to represent companies, investors, funding rounds, and news, with provenance tracked for each fact.
Construct a unified, reliable data backbone that serves as the single source of truth for all campaigns, AI agents, and product features.

Fully remote and asynchronous work environment.
Partial overlap with US Eastern time zone required, but not full-time US hours.
Meetings are grouped on Mondays and Thursdays to preserve uninterrupted focus time the rest of the week.
Access to premium AI development tools including paid subscriptions to Claude Code, Cursor, and leading AI models.
Collaborate directly with the GTM lead and founding engineering team, where your data systems directly enable all product and campaign development.

Remote (Worldwide)

The database itself: Postgres and Supabase with hybrid search, schema design, modeling, scaling, and performance as it grows without a ceiling. The agents that read it run on Pydantic AI and the Claude Agent SDK, on AWS. We are consolidating into pgvector, not buying a vector DB.
Data quality end to end: validation gates for vendor and third-party data, dedup, entity resolution, provenance, monitoring.
The communications layer: raw emails and call transcripts stored, linked to the right people and companies, and searchable.
Ingestion and enrichment pipelines: funding rounds, market news, and contact and company research at scale, engineered for cost and freshness.
The knowledge graph: companies, investors, funding rounds, and news as entities and relationships - node and edge tables in Postgres, provenance on every fact.
The unified data layer: one clean spine that every campaign, agent, and product feature reads from.

Fully remote and async.
Your day overlaps with US Eastern time for a few hours - not full US hours.
Meetings batch on Mondays and Thursdays, the rest is deep work.
The best AI tooling, paid (Claude Code, Cursor, top models).
You work alongside our GTM lead and our founding engineers, and your layer feeds everything they build.

Paires is hiring a Data Engineer