Senior Analytics Engineer - CANADA

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 that has hit $100M in annual recurring revenue. More than 90,000 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 Role We're looking for a Senior Analytics Engineer to build and scale the analytical foundation that powers decision-making across Go-to-Market, Product, Finance, People, and Operations teams. You will sit at the intersection of data engineering and analytics: transforming raw product, marketing, financial, and operational data into clean, well-modeled, and trustworthy datasets. Your work will power everything from executive dashboards and cohort analyses to experimentation, billing operations, AI-powered outreach, and semantic layers that let AI agents answer stakeholder questions autonomously. This is a highly cross-functional role — you'll partner closely with Product Management, Marketing, RevOps, Finance, People Ops, and Engineering to ensure our analytics stack is robust, scalable, and aligned with the business. Responsibilities Build & Own the Data Foundation Own and evolve our dbt project — ensuring models are performant, well-tested, and documented. Design and maintain the Snowflake data warehouse and ingestion processes. Use modern data modeling best practices to create core entities and datasets that account for complex business processes and logic. Build and maintain custom Python/Airflow pipelines to ingest data from third-party APIs into Snowflake. Design and operate cross-system reconciliation models that compare data across source systems to surface discrepancies and protect revenue. Drive Data Quality & Automation Implement testing and observability for analytics pipelines. Enforce CI/CD best practices, such as automation, linting, tests, code review and approvals. Standardize metric definitions and ensure they are consistently computed across tools. Investigate and document data incidents end-to-end — from root cause analysis through remediation tracking and stakeholder communication. Cross-Functional Collaboration Act as data liaison between Engineering, GTM, and Finance — ensuring consistent metric definitions and proper system instrumentation. Enable stakeholder self-service access to trusted insights. Drive data literacy: evangelize best practices in querying, dashboarding, and interpreting metrics; coach stakeholders toward self-serve. Build AI-Ready Data Infrastructure Design and maintain Snowflake Cortex semantic views that serve as the governed data interface for AI agents and LLM-powered tools. Partner with AI/product teams to scope, build, and validate the semantic layer definitions that power internal AI assistants. Build measurement frameworks for AI-powered initiatives — including experiment design and attribution modeling. Qualifications Must Hav