Senior Analytics Engineer

16 hours ago

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Luxury Presence

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Real Estate • Marketing

Luxury Presence is a company that specializes in providing real estate professionals with top-tier digital solutions. They offer award-winning real estate website designs and expert marketing solutions aimed at helping agents, teams, and brokerages grow their business and build their brand. Their platform includes tools for IDX home search, property websites, digital CMA, SEO services, content marketing, advertising, and social media management. Trusted by over 20 of the top 100 Wall Street Journal agents, Luxury Presence empowers real estate professionals to attract more business through beautiful and functional digital experiences.

201 - 500 employees

🏠 Real Estate

📋 Description

• 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. • 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. • 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.

🎯 Requirements

• 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. • 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. • 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. • Proficiency in Python for deeper analysis and automation (Nice to Have). • Experience building and maintaining Airflow DAGs (Nice to Have). • Experience with Spark and PySpark (Nice to Have).