Lead Data Engineer

Lead Data Engineer

Location:

Remote within Quebec, Ontario, or Nova Scotia, Canada

Reports to:

CTO

Use of AI in our hiring process

Trolley uses AI-assisted tools to help support certain aspects of our recruitment process, including screening and assessing applications against the qualifications and requirements of a role. These tools are designed to support our Talent Acquisition team and improve the efficiency and consistency of our hiring process. AI does not make final hiring decisions. All hiring decisions involve human review and judgment.

About us

Trolley is the payouts platform for the internet economy. Our mission is to unlock the global economic opportunity of the internet by building a truly borderless payouts ecosystem.

Through our platform and API, Trolley enables businesses to pay people anywhere in the world, supporting creators, on demand workers, and suppliers at scale. Companies rely on Trolley as mission-critical infrastructure to automate payouts, collect tax and banking information, and reduce fraud and risk, all in one place.

Today, Trolley is the trusted payouts solution for hundreds of businesses, including Canva, Soundcloud, and Envato. We've processed millions of payments globally, helping creators, artists, and suppliers get paid quickly, securely, and with confidence.

As Trolley enters its next stage of growth, we're investing heavily in AI to accelerate product innovation, improve operational efficiency, and transform how software is built across the company.

The Opportunity

Data sits under everything Trolley does: the finance close, the reporting our customers see, and the fraud signals that keep payouts safe. We're looking for a Lead Data Engineer to own that platform, lead our data team, and help us put data to work with AI.

This is a player-coach role. Most of your time is hands-on: keeping the pipelines, warehouse and reporting the business runs on healthy and trusted, and finding where data and AI can make our product better and our people faster. You'll also manage and develop one data engineer today, with room to grow the team and your leadership as Trolley's data needs grow.

What You'll Do

• Lead the data team
• Manage, coach and develop the data engineer on your team, with regular one to ones and clear goals.
• Set the standards for how we build: code review, testing, documentation and on-call for data.
• Plan the team's work with Engineering, Finance and Product, and work collaboratively when priorities shift.
• Help shape the team as it grows, including hiring if and when the time comes.
• Own Trolley's data platform
• Own our Databricks lakehouse end to end: ingestion, modelling, quality and cost.
• Build and run pipelines from our production platform, Salesforce, NetSuite and third-party sources.
• Keep internal reporting in Sigma accurate, fast and self-serve.
• Make pipelines observable and recoverable, so failures are loud, owned and quick to fix.
• Partner with Finance
• Run the data behind month-end close, revenue calculations and vendor cost reconciliation.
• Work with Finance so they own the definitions and we own the pipeline.
• Support audits and year-end reconciliation with data people can trust.
• Build data into the product
• Build and improve customer-facing data products, including our data connector and embedded reporting.
• Work with Engineering and Product on data features like fraud and risk signals.
• Put data to work with AI
• Build the data foundations that let AI tools and agents work safely with Trolley's context: engineering, operational and business data, with the right guardrails.
• Use AI in your own work to build, test and document pipelines faster.
• Find where data and AI can improve the product and how our teams work, and make the case with evidence.
• Help us measure engineering delivery by bringing tools like Jira and GitHub into the warehouse.
• Keep data safe
• Apply Trolley's data management and privacy policies in everything you build, including what data may and may not reach AI tools.
• Partner with InfoSec and Compliance on access, retention and audit requirements.

What We're Looking For

• Required Experience
• 7+ years in data engineering, with ownership of a production data platform.
• Experience leading other engineers: managing, mentoring or leading a small team day to day.
• Deep experience with Databricks or a similar lakehouse, SQL, and Python.
• Experience building reliable pipelines from operational databases and SaaS systems.
• Experience supporting finance or accounting processes with data.
• Hands-on use of AI tools in your own engineering work, and clear thinking about where AI helps and where it doesn't.
• Comfortable as the most senior data person in the company, with a lot of autonomy.
• Preferred Experience
• Formal people management, and interest in growing a team over time.
• Fintech, payments or other regulated environments.
• Customer-facing data products, embedded analytics or data sharing.
• Building context layers, retrieval or data pipelines for AI agents.
• Data governance and privacy in practice: PII handling, access control, GDPR.
• This job posting is for an existing vacancy.

What we offer

Join an amazing team of diverse people working together on a common mission.

Competitive salary

ESOP Program: Meaningful equity and ownership that aligns your success with ours

Extended healthcare benefits from Day 1.

4 weeks paid vacation per year + public holidays (+ 1 extra vacation day per year of service).

30 days remote work from anywhere.

Gym membership allowance.

1/2 day Fridays off during summer.

Company-provided use of Apple MacBook and Mac gear.