Senior Analytics Engineer

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Luxury Presence

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏠 Real Estate

📣 Marketing

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.

📋 Description

• Build and own the dbt project, ensuring models are performant, well-tested, and documented • Design and maintain the Snowflake data warehouse and ingestion processes • Create core entities and datasets using modern data modeling best practices • Build and maintain custom Python/Airflow pipelines for third-party API ingestion into Snowflake • Design and operate cross-system reconciliation models to surface discrepancies and protect revenue • Implement testing and observability for analytics pipelines • Enforce CI/CD practices including automation, linting, tests, code review, and approvals • Standardize metric definitions across tools • Investigate and document data incidents from root-cause analysis through remediation and stakeholder communication • Act as data liaison between Engineering, GTM, and Finance • Enable stakeholder self-service access to trusted insights and promote data literacy • Design and maintain Snowflake Cortex semantic views for AI agents and LLM-powered tools • Partner with AI/product teams on semantic-layer definitions for internal AI assistants • Build measurement frameworks for AI initiatives, including experiment design and attribution modeling • Establish trusted analytics layers, improve data quality and reliability, reduce time-to-insight, quantify discrepancies, and define success metrics for new initiatives

🎯 Requirements

• 5+ years of experience as an analytics engineer, data engineer, or 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 opportunities, contracts, subscriptions, cases, and field history data • Experience building custom ELT pipelines from third-party APIs into a cloud data warehouse • Experience designing cross-system reconciliation models across multiple source systems • Experience with event-based and product usage data such as PostHog or Mixpanel • Experience connecting paid advertising, campaign, and attribution data to product analytics • Experience designing and maintaining governed semantic layers such as dbt Semantic Layer or Snowflake Cortex • Comfort with large-scale data systems including Snowflake, BigQuery, or Redshift • Familiarity with CI/CD, Git-based workflows, and automated testing • Experience collaborating with engineers, analysts, and product managers • Demonstrated success using analytics to drive decisions in technical or product-focused environments • Comfort taking ownership of ambiguous problems and designing end-to-end solutions • Nice to have: Airflow DAGs, statistics and experiment design, predictive modeling, financial SaaS metrics and billing operations, and people analytics