Senior / Staff Data Engineer | AWS, dbt, Snowflake, Databricks | Remote Canada | Top Pay + Equity

"You miss 100% of the pipelines you don't build."

(Wayne Gretzky, probably, if he'd gone into data)

So what are the three key parts of this role?

1. Build the platform, not just the pipelines

The data team is currently one person. You'll be number two, and a genuine partner to the data lead.

The foundations are in: Snowflake, Databricks, dbt and early LLM pipelines. Now they need someone to turn them into a platform that scales. This role is weighted towards infrastructure, distributed systems and platform engineering rather than data modelling. You'll make the architecture calls, choose the tooling and keep the platform flexible as AI reshapes the landscape.

2. Turn data into products customers rely on

Here, data isn't a reporting function. It's a feature.

You'll build an agentic semantic layer, event-driven data products and embedded analytics that customers use every day. You'll also lead zero-to-one work in streaming, governance and knowledge management. The data arrives from thousands of external systems that each interpret the rules their own way, so making it trustworthy is the real craft.

3. Run what you build

Infrastructure as code, on-call, incident response and production reliability on AWS are yours. So are large parts of the data function itself, from pipeline design through to stakeholder-facing analytics, while keeping day-to-day requests in check so the big work still ships.

Who you'd be working for

We can't name them yet, but here's the picture.

They're an AI-first B2B software company fixing a problem most people never notice but every business feels: getting company systems to exchange orders, invoices and shipment data with each other. Each new connection between a brand, retailer or logistics partner used to take months of manual setup. Their self-service platform, AI-powered rules engine and pre-connected network cut that to minutes.

• Hundreds of customers, from Fortune 500 enterprises to well-known consumer brands
• Hundreds of millions of transactions across thousands of trading partnerships
• Ranked number one in its category across major industry reports
• Backed by top-tier Silicon Valley and supply chain investors
• Around 100 people across North America, including a Canadian presence in Vancouver

Why is it a great place to work? Every transaction on the platform is a data problem, so your work lands directly with customers. The company has real scale and revenue, yet it's small enough that one strong data engineer changes its trajectory. Leadership is accessible, decisions are quick and the hiring manager is one of the most responsive we've worked with.

And it's genuinely remote. Vancouver, Toronto, Montreal, Calgary, Ottawa or a lake cottage with decent Wi-Fi. If you live in Canada, you're in range.

What this role IS

It's for a full-stack data engineer, meaning the whole data stack, from infrastructure through to the customer.

It's for someone who has built a data platform from zero and then scaled it. Ideally you were an early data hire at a startup and can show what you built and the numbers that prove it grew.

It's for a generalist with depth, equally at home designing event-driven infrastructure and working out what stakeholders actually need.

And it's for someone who uses AI seriously. Expect to be asked exactly how AI tools multiply your output, with real, measurable examples. Dabbling doesn't count.

What this role is NOT

This is where most applicants miss. Every point below comes straight from real hiring feedback.

• Deep specialists in one niche (performance tuning, migrations, ontology) who haven't owned the wider stack
• Looking after someone else's ETL, or living in SQL inside a mature warehouse
• Writing dbt models in someone else's architecture, or building dashboards
• Careers spent only inside large corporates. Startup experience matters
• Contractors or consultants who shipped a project and left
• Scattered project work with no production on-call or infrastructure as code
• Engineers who can't explain how they use AI to work smarter. That alone has stopped strong Principal and Staff candidates
• A senior title doing the heavy lifting on your resume

Resumes without clear ownership and zero-to-one delivery are declined immediately, whatever the seniority or brand names. Vague bullet points get the same result.

What you'll bring

• 5+ years building and operating data platforms
• Pipelines designed and built as distributed systems
• Production dbt or an equivalent transformation framework
• Production Snowflake, Databricks, BigQuery or similar
• Hands-on AWS (GCP or Azure fine), including on-call, incident response and infrastructure as code
• Customer-facing or embedded analytics you built and shipped
• Early data engineering at a startup that went on to scale, with metrics to back it
• For Staff level, evidence of setting technical direction and managing stakeholders

Nice to have: a numerical background (engineering, physics, maths or CS), streaming with Kafka or Kinesis, and experience taming messy, unstructured data.

Why it's worth your time

Engineer number two, not number 40. A lead who wants a partner. Data that is the product, not the plumbing. Fully remote anywhere in Canada, with a highly competitive salary and meaningful equity for the right person.

How to apply

Send your resume with a short note covering:

1. The data platform or product you're proudest of building from zero, and what happened to it
2. How you use AI in your daily engineering work, with a real example of the impact
3. Your Canadian work authorisation status (see below)

Work authorisation: please read before applying

This role is open only to Canadian citizens and permanent residents already living in Canada.

There is no visa or work permit sponsorship of any kind. No LMIA, no employer-specific work permits, no work permit extensions or transfers, and no future permanent residency sponsorship.

No exceptions.

If you need sponsorship now or at any point in the future, we can't put you forward.