Analytics Engineer

About Greystar

Greystar is a leading, fully integrated global real estate platform offering expertise in property management, investment management, development, and construction services in institutional-quality rental housing. Headquartered in Charleston, South Carolina, Greystar manages and operates over $350 billion of real estate in more than 260 markets globally with offices throughout North America, Europe, South America, and the Asia-Pacific region. Greystar is the largest operator of apartments in the United States, managing over one million units/beds globally.

Across its platforms, Greystar has nearly $79 billion of assets under management, including over $34 billion of development assets and over $36.5 billion of regulatory assets under management. Greystar was founded by Bob Faith in 1993 to become a provider of world-class service in the rental residential real estate business. To learn more, visit

Greystar is a leading, fully integrated global real estate platform offering expertise in property management, investment management, development, and construction services in institutional-quality rental housing. Headquartered in Charleston, South Carolina, Greystar manages and operates over $350 billion of real estate in more than 260 markets globally with offices throughout North America, Europe, South America, and the Asia-Pacific region. Greystar is the largest operator of apartments in the United States, managing over one million units/beds globally.

Across its platforms, Greystar has nearly $79 billion of assets under management, including over $34 billion of development assets and over $36.5 billion of regulatory assets under management. Greystar was founded by Bob Faith in 1993 to become a provider of world-class service in the rental residential real estate business. To learn more, visit

Greystar's D²AI organization (Data, Digital, and AI) is responsible for the platforms, processes, and practices that power analytics and AI across the company. This role sits on Decision Intelligence, the team within D²AI that turns that capability into better business decisions. The name is the mandate: we exist to make the company's decisions faster, sharper, and better informed, not simply to produce reports.

We require AI fluency because this role sits at the intersection of data, technology, and business outcomes. That means understanding how AI systems are designed and operationalized, using AI-enabled tools in your day-to-day work, and partnering effectively with engineering, analytics, and business teams so the solutions we ship are reliable, responsible, and impactful.

Greystar is building the data foundation that will power the most AI-advanced operator in global multifamily real estate. As an Analytics Engineer on one of Decision Intelligence's forward-deployed pods, you'll turn that foundation into working data products that a business team uses to make decisions every day, whether those are traditional dashboards, predictive models, or lightweight web apps. Our team includes engineers, designers, and product leaders with experience from Google, Microsoft, Airbnb, Strava, and Amazon.

• Take assigned initiatives from the original business question through a data product people actually use to decide, staying with the work through deployment and handoff.
• Embed inside your assigned area of the business, learning its goals, data, and workflows well enough to spot the highest-value opportunities yourself.
• As your understanding deepens, bring the business proactive recommendations, not just answers to the questions it already knows to ask.
• Default to doing it right; when speed is genuinely required, ship a usable solution with a documented path back to the governed, certified standard.

• Ship a working data product quickly, ranging from a dashboard to a statistical model to a lightweight web app, then iterate live with the people who will use it.
• Build and maintain the data models behind those products in Databricks and SQL, with real rigor around grain, keys, and referential integrity so results hold up under scrutiny.
• Design sound experiments and measurement plans to establish baselines and prove out program impact, keeping correlation and causation distinct.
• Present findings, trade-offs, and recommendations to stakeholders ranging from on-site operators to senior leaders and executives, tailoring the message to the audience.
• Identify which products are worth graduating to shared platforms such as the Greystar Performance System (GPS), our platform for enterprise reporting, and Podium, our internally built platform for enabling and governing AI use. Partner with platform teams to scale them enterprise-wide.
• Contribute reusable patterns, tooling, and documentation that raise the speed and quality of every pod. We treat documentation as part of delivery, not an afterthought.