Senior Analytics Engineer

🕒 August 10

🇺🇸 United States – Remote

💵 $150k - $190k / year

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 2%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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 analytical data foundation supporting Go-to-Market, Product, Finance, People, and Operations decision-making • Own and evolve the dbt project, ensuring models are performant, tested, and documented • Design and maintain the Snowflake data warehouse and ingestion processes • Create well-modeled core entities and datasets for complex business processes • Build and maintain custom Python/Airflow pipelines ingesting third-party API data into Snowflake • Design and operate cross-system reconciliation models to identify discrepancies and protect revenue • Implement pipeline testing, observability, CI/CD, linting, code review, and approvals • Standardize metric definitions across tools and investigate data incidents through remediation • Liaise across Engineering, GTM, Finance, Product, Marketing, RevOps, and People Ops • 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 and product teams on semantic-layer definitions and measurement frameworks • Define experiment design, attribution modeling, and success metrics for AI-powered initiatives • Establish trusted analytics layers, improve data quality and reliability, reduce time-to-insight, and resolve cross-system discrepancies

🎯 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 involving joining, deduplication, and data comparison • 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 • Strong 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 and multi-source API ingestion pipelines • Nice to have: Statistics, A/B testing, significance testing, and incremental-impact measurement • Nice to have: Predictive modeling fundamentals, including classification, feature selection, and model evaluation • Nice to have: Financial SaaS metrics and billing operations • Nice to have: People analytics