P
Paires
1-10 employees
internet
consumer-internet
consumers
information-technology
leisure
marketplaces
online-travel
rental-housing
services
social-network
tourism
travel
About Paires
A refreshing new and personalized social platform and housing marketplace to match roommates and simplify house-hunting process. 'Housing Made Personal'.
2 days ago
Data Engineer
Full-time
Mid Level
Data Engineer
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Description
- We are hiring our first Data Engineer to own the database our agents and outreach are built on.
- Paires is where founders come to raise capital.
- We pair them with the right investors from a large, engaged global investor network, then run the warm outreach that turns into meetings.
- It is a two-sided platform, live with paying clients, profitable and self-funded, built by a small, senior, flat team that ships fast.
- Everything we do runs on one asset: a database of every company and investor out there, every funding round, the news that matters, and how they all connect - plus the raw context underneath: every email and call transcript, linked to the right people and companies.
- It is a knowledge graph and a memory in one.
- Our matching, our outreach, and our agents are built on top of it, and it grows faster than anyone can own it on the side.
- You become its owner.
- You design it, scale it, keep it clean, and turn it into the single source of truth that everything reads from.
- To be clear about the shape of this seat: it is not a reporting or analytics warehouse.
- It is the memory a live product thinks with, built for one reader above all: agents retrieving exactly the right fact at the right moment.
- One honest filter before you apply: if the database you are proudest of tracked shipments, sensors, factory lines, or compliance - however well you built it - that is a different seat.
- If it tracked companies, investors, deals, and the people and conversations around them, keep reading.
- 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.
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Requirements
- Have owned a database of companies, people, deals, or the communications between them - a CRM source of truth, a market or deal intelligence graph, an enrichment layer - that a live product, agents, or a sales team read from.
- Are strong in SQL and Python, with real pipeline work behind you: ingest, transform, dedup, enrich.
- Have caught bad data before it hurt the business, and can tell us how.
- Think in schemas and contracts, and design for the queries of a year from now.
- Have modeled entities and relationships at scale - companies to investors to rounds to people - and kept the connections queryable as the sources multiplied.
- Move fast with AI tooling and own outcomes.
- You do not need the title. If you were the RevOps or growth person who owned the CRM data, the enrichment pipelines, and the dedup nobody else wanted - and you got real hands-on with AI - we want to hear from you.
- Bonus: pgvector and embeddings, a knowledge graph you modeled in a relational database, funding-round or news ingestion at scale, entity resolution at scale, a raw communications store you built yourself.
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Benefits
- 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.