Data Engineer →

Topsail; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Topsail is seeking a data engineer to own the ontology and the data pipelines that underlie every deployment. Remote (US) with occasional travel; reports to the founders.

You will model business data across ERPs, CRMs, spreadsheets, and emails, delivering a governed, queryable data layer that teams can rely on.

As part of a forward‑deployed team, you will reuse patterns across clients and keep the stack on the client’s own domain.

Qualifications

• You have built and run data systems that a real business depends on.
• You think in data models and have designed schemas for real domains.
• SQL and relational modeling are home for you and you are fluent in a modern language for pipelines.
• You already use AI in your own work and understand what agents need from data.
• You write clearly and can explain a model to the operator whose business it describes.

Responsibilities

• Design ontologies for real business domains: entities, relationships, and rules.
• Build pipelines: ingest from ERPs, CRMs, spreadsheets, email; perform entity resolution and drift checks.
• Make the foundation queryable by agents with well‑modeled relational data and MCP endpoints.
• Keep it model‑agnostic and client‑owned; work on the client's stack to preserve ownership.
• Turn repeatable patterns into tooling the team reuses across clients.

Skills

Data modeling

SQL

ETL pipelines

Entity resolution

Relational databases

Python

Tools

NetSuite

Salesforce

Procore

Airflow

dbt

Job description

Own the ontology and the data pipelines every deployment stands on. Not client‑facing by default. The part of the stack everything else depends on.

Full‑time Remote (US) Occasional travel Reports to the founders

Every Topsail engagement starts with the same move: model the business as it actually runs and install that ontology as the layer every system and every AI tool reads from. A data engineer here owns that foundation. You take a company's spreadsheets, ERP, CRM, email, and tribal knowledge and turn them into a resolved, governed data model with pipelines that keep it true.

This is not a client‑facing role by default. You work with the forward‑deployed engineers and strategists who are inside the client, and you own the part of the stack that everything else depends on.

What you will do

• Design ontologies for real business domains: the entities, relationships, and rules a staffing company, a construction firm, or an investment firm actually runs on.
• Build the pipelines that populate and maintain them. Ingestion from ERPs, CRMs, spreadsheets, and email, entity resolution over ugly data, and the checks that catch drift before a client does.
• Make the foundation queryable by agents and people: well‑modeled relational data, retrieval‑ready structures, and MCP endpoints that answer questions in plain language with sources.
• Keep it model‑agnostic and client‑owned. Everything you build lives on the client's stack and is theirs to keep.
• Turn what works at one client into patterns and tooling the whole team reuses at the next.

What we look for

• You have built and run data systems that a real business depends on. We will ask about the ugliest source you ever reconciled and how you kept it honest.
• You think in data models. You have designed schemas for a real domain, done entity resolution at scale, and know where an ontology earns its keep and where it is overkill.
• SQL and relational modeling are home for you, and you are fluent in a modern language for the pipelines around it.
• You already use AI in your own work and understand what agents need from data: clean identities, sourced facts, and structures they can retrieve over.
• You write clearly and can explain a model to the operator whose business it describes.

Nice to have

• Experience with transformation frameworks, orchestration tools, or event‑driven pipelines.
• Time with ERPs or CRMs from the inside: NetSuite, Salesforce, Procore, or their peers.
• Familiarity with retrieval systems, embeddings, or knowledge graphs.

What you get

• Systems that run inside real businesses, owned by you end to end.
• A new industry and a new data problem every few months, next to the people who built the company.
• Remote‑first, with time in New York, San Francisco, Boston, and Lehi, Utah when it matters.
• A serious AI budget: frontier model access, the tools you want, and a lot of tokens.

Compensation: Above‑market salary and bonus, plus meaningful equity.