Staff Analytics Engineer - CANADA (Remote)

Confirmed live in the last 24 hours

Luxury Presence

Canada

Remote

Posted March 31, 2026

Job Description

Luxury Presence is building the AI growth platform for real estate. Backed by Bessemer Venture Partners and other top investors, we're a Series C company on track to hit $100M in annual recurring revenue in the next six months. More than 87,000 real estate professionals, including over 30% of the WSJ Real Trends top 100 agents in the United States, use us to run and grow their business.

The Opportunity

We don't just use AI. We build with it, ship with it, and think with it. We're in the top 1% of companies applying AI effectively, not just to our products, but to how we build them. With an unlimited budget for Anthropic tokens, our engineers use AI agents to write, review, and ship production code every day. We're building toward a world where humans design systems and AI builds them, and we're already further along that path than almost anyone else.

As a Staff Analytics Engineer, you'll be a technical leader at the center of this transformation. You'll shape platform architecture, drive AI-powered product delivery, and raise the bar for what a small, AI-augmented engineering team can accomplish. This is a role for someone who already lives in their terminal with AI, who has strong opinions about how AI changes system design, and who wants to help define what a next-generation engineering organization looks like.

What You'll Do

Own and evolve a tool-agnostic analytics layer powering business decisions. Design and maintain scalable, well-modeled datasets using dbt, Snowflake, and a semantic layer—transforming raw data into trusted, high-quality metrics used across Product, GTM, Finance, and Operations.

Partner deeply with analysts and business stakeholders. Collaborate with Data Analysts, Product, and business leaders to define metrics, enable self-service analytics, and deliver insights that directly impact decision-making and product development.

Drive data quality, consistency, and trust at scale. Implement robust testing, monitoring, and validation frameworks to ensure data accuracy and reliability, while standardizing metric definitions across the organization.

Build data products and AI-powered analytics systems. Develop systems such as AI-driven support ticket classification and contribute to building an AI agent that can act as a Data Analyst—leveraging the semantic layer to answer business questions and generate insights.