Data Engineer

Paires

2d•CA$150,000 - CA$250,000•Remote

About The Position

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.

Requirements

Owned a database of companies, people, deals, or the communications between them (e.g., 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.
Strong in SQL and Python.
Experience with pipeline work: ingest, transform, dedup, enrich.
Experience catching bad data before it hurt the business.
Ability to think in schemas and contracts, and design for future queries.
Experience modeling entities and relationships at scale (companies to investors to rounds to people) and keeping connections queryable.
Ability to move fast with AI tooling and own outcomes.

Nice To Haves

Experience with pgvector and embeddings.
Experience modeling a knowledge graph in a relational database.
Experience with funding-round or news ingestion at scale.
Experience with entity resolution at scale.
Experience building a raw communications store.

Responsibilities

Own the database our agents and outreach are built on.
Design, scale, and maintain the database as the single source of truth.
Ensure data quality end to end, including validation gates for vendor and third-party data, dedup, entity resolution, provenance, and monitoring.
Manage the communications layer, ensuring raw emails and call transcripts are stored, linked, and searchable.
Build and maintain ingestion and enrichment pipelines for funding rounds, market news, and contact and company research.
Develop and manage the knowledge graph, representing companies, investors, funding rounds, and news as entities and relationships.
Create and maintain the unified data layer that all campaign, agent, and product features read from.