Senior Analytics Engineer - Canada

**[Luxury Presence](https://himalayas.app/companies/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 Have:** * 5+ years of experience as an analytics engineer, data engineer, or a similar role in a SaaS environment. * Deep expertise in SQL, dbt, and modern data modeling best practices. * Proficiency in Python for pipeline development, API integrations, and automation. * Experience modeling Salesforce data — opportunities, contracts, subscriptions, cases, and field history. * Proven experience building custom ELT pipelines that ingest data from third-party APIs into a cloud data warehouse. * Experience designing cross-system reconciliation models — joining, deduplicating, and comparing data across multiple source systems to surface discrepancies. * Proven experience working with event-based and product usage data (e.g., Posthog, Mixpanel). * Experience connecting marketing data (paid ads, campaigns, attribution) to product analytics — ideally having built end-to-end pipelines from ad platforms through to conversion and retention metrics. * Experience designing and maintaining semantic layers that serve as governed data interfaces (dbt Semantic Layer, Snowflake Cortex, or similar). * Comfortable with large-scale data systems (Snowflake, BigQuery, Redshift). * Strong familiarity with CI/CD, Git-based workflows, and automated testing. * Experience collaborating cross-functionally with engineers, analysts, and product managers. * Demonstrated success using analytics to drive decisions in a technical or product-focused environment. * Comfort taking ownership of ambiguous problems and designing end-to-end solutions. ### **Nice to Have:** * Experience building and maintaining Airflow DAGs and orchestrating multi-source API ingestion pipelines. * Strong foundation in statistics and experiment design — A/B testing, significance testing, and measuring incremental impact. * Experience with predictive modeling fundamentals — classification, feature selection, and model evaluation. * Familiarity with financial SaaS metrics and billing operations (ARR/MRR/NRR, subscription reconciliation, revenue recognition). * Experience with people analytics (headcount, attrition, compensation benchmarking). ### **What Success Looks Like** * Establish a trusted, well-modeled analytics layer that product managers, marketers, and leaders rely on daily. * Improve data quality and reliability, with clear SLAs and observability around our most critical models. * Drive down time-to-insight by enabling self-serve access to high-quality datasets and metrics. * Extreme ownership over critical infrastructure and data models that directly impact product decisions and business growth. * Partner with data engineers and analysts to build a semantic layer that AI agents can use to answer stakeholder questions — and actively maintain the semantic views that power those agents. * Proactively identify and quantify data discrepancies across systems and drive them to resolution with operational teams. * Design measurement frameworks for new initiatives — defining what to track, how to measure impact, and what "success" means before launch. ### Join us in shaping the future of real estate The real estate industry is in the midst of a seismic shift, and the future belongs to those who break new ground. As one of the fastest-growing companies in the proptech and marketing sectors, [Luxury Presence](https://himalayas.app/companies/luxury-presence) challenges the status quo of what technology can do for real estate agents, leaders, and brokerages. We're a team of agile and tenacious innovators working collaboratively to drive the industry forward. Together, we build game-changing products that empower modern real estate entrepreneurs to dominate their markets. From award-winning web design to agile SEO solutions to cutting-edge AI tools, we deliver tech that anticipates market shifts and keeps our clients ahead of their competition. Founded in 2016 by Stanford Business School alum Malte Kramer, [Luxury Presence](https://himalayas.app/companies/luxury-presence) has grown to a global team ranked on the Inc. 5000 fastest-growing companies list three years in a row. We're backed by world-class investors, including Bessemer Venture Partners, NextEquity Partners, Toba Capital, and Switch Ventures, and have raised $89 million to date. More than 18,000 real estate businesses rely on our platform, including 30% of the Wall Street Journal RealTrends top agents and teams. Additionally, many of the industry's most powerful brokerages rely on [Luxury Presence](https://himalayas.app/companies/luxury-presence) as a trusted business partner. Every year since 2020, [Luxury Presence](https://himalayas.app/companies/luxury-presence) has ranked on BuiltIn's Best Place to Work lists. HousingWire named our founder and CEO a 2024 Tech Trendsetter, we've received several Tech100 Awards, and we just scored an Inman Innovation Award for Best AI-Powered Platform. **[Luxury Presence](https://himalayas.app/companies/luxury-presence) is an Equal Opportunity Employer.** All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Originally posted on [Himalayas](https://himalayas.app)