Senior Data Engineer, AI & Data Platform

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 .

JOB DESCRIPTION SUMMARY

Greystars D2AI team is responsible for the platforms processes and practices that power AI across the organization. This role goes beyond traditional delivery: your decisions influence how data is transformed into intelligent scalable solutions used by teams company-wide. 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 day-to-day work and partnering effectively with engineering analytics and business teams to ensure AI solutions are reliable responsible and impactful.

We hire for Greystar not for a single team. Youll join a fast paced engineering group and get to work across many initiatives as we modernize and rethink how the company operates. That range is the benefit: broad exposure to the business real variety in the problems you solve and the chance to help shape a multi-billion dollar global operator rather than maintain one corner of it. Once youre assigned to a project we expect you to own your piece end to end and then move on to the next. The engineers who thrive here are versatile self-directed and able to pick up unfamiliar business context quickly.

In addition to your resume we suggest that candidates include a short video (2-5 min) demonstrating how you have used AI tools in your engineering workflow: code generation debugging architecture documentation or similar. We recommend recording with Loom (free) or uploading as an unlisted
YouTube video.

Please embed this link at the top of your resume. Applications with a video link will be prioritized

JOB DESCRIPTION

Greystar is building the data foundation that will power the most AI-advanced operator in globalmultifamily real estate. Were seeking a Senior Data Engineer to design build and operate the core datainfrastructure that enables AI-powered products analytics and decision-making across a multi-billiondollar global portfolio.

This role sits at the intersection of data engineering and applied AI: youll build the pipelines platformsand interfaces that make Greystars proprietary data accessible trustworthy and AI-ready. You will workacross our Data Management Platform (DMP) MCP integrations and AI-enabled analytics tools that
serve every business unit. Our team includes engineers designers and product leaders with experiencefrom Google Microsoft Airbnb Strava Amazon and more.

You wont be boxed into one standing domain. Once youre assigned youll take a project from ingestionthrough certified gold data and into production hand it cleanly to operations and then move to the initiatives will play to a deep specialty; others will ask you to learn a new part of the business with that kind of movement is part of the job.

What Youll Do
Own Initiatives End to End
Take assigned initiatives from raw ingestion through bronze silver and certified gold stayingwith the work through deployment and handoff to operations.
Redeploy across projects as priorities shift ramping quickly on unfamiliar source systems andbusiness domains.
Default to doing it right; when speed is genuinely required ship a usable solution with adocumented path back to the governed gold standard.

Build and Scale AI-Ready Data Infrastructure
Design build and maintain scalable and self-healing data pipelines that ingest transform andserve data from dozens of source systems (PMS CRM financial systems IoT web/mobileanalytics and third-party providers).
Develop and operate our Data Marketplace (DMP) on Databricks ensuring data is governedvalidated maintains high data quality and available for AI/ML workloads.
Build data models with real rigor: correct grain natural and foreign keys and referential integrityso downstream AI tools (like MCP) and Data Catalog applications can navigate relationshipsreliably.
Build models optimized for both analytical queries and AI consumption including feature storesembedding pipelines and real-time serving layers.
Implement data quality frameworks including automated testing lineage tracking anomalydetection and regression testing for critical data assets.
Enable AI and MCP Integrations
Build and maintain MCP (Model Context Protocol) server integrations that expose Greystars datato LLM-powered tools and AI agents across the organization.
Design APIs and data interfaces that let AI products (GPS internal tools) queryand act on data in real time. Exposure to full-stack or application development for exampleAzure Web Apps built to scale to thousands of users is a strong plus.
Partner with Data Science and Product teams to operationalize ML models building theinfrastructure for training evaluation deployment and monitoring.
Evaluate and integrate AI-powered data tooling (AI-assisted cataloging automated schemadetection intelligent data quality monitoring).
Collaborate with other engineers on AI integration patterns prompt engineering and moderndevelopment practices. We are an AI-forward team and its moving fast so we test iterate shareand repeat.

Drive Data Governance and Trust
Implement and enforce data governance policies including access controls PII handling dataclassification and compliance requirements across global operations.
Build observability into data systems: monitoring alerting SLA tracking and data freshnessguarantees.
Contribute to Greystars AI governance framework ensuring data used by AI systems is accuratecompliant and appropriately scoped.
Document data models pipeline architectures and integration patterns so the work is reusableand the next engineer or a business-unit analytics team can self-serve. We treat documentationas part of delivery not an afterthought.

What You Bring
Data Engineering Excellence
5 years of professional data engineering experience building and operating production dataplatforms.
Deep expertise with Databricks Spark or similar distributed data processing frameworks.
Strong SQL skills and data modeling experience across analytical (star schema data vault) andAI/ML workloads with a firm grasp of keys grain referential integrity data quality and what ittakes to certify a gold data asset.
Deep experience with AI coding tools like Cursor Codex Claude Code etc.
Proficiency in Python; experience with orchestration tools (Airflow Dagster or DatabricksWorkflows).
Experience with cloud data platforms (ADLS Synapse Azure ML; AWS/GCP acceptable) andrelational back ends such as Postgres.

AI/ML Data Infrastructure
Experience building data infrastructure that supports ML workflows: feature stores trainingpipelines embedding generation and model serving.
Familiarity with LLM integration patterns including RAG architectures vector databases(Pinecone Weaviate or similar) and MCP or tool-use frameworks.
Understanding of how AI/ML models consume data and the engineering requirements forreliable low-latency AI data serving.
Awareness of AI governance considerations: data provenance bias detection and responsible AIdata practices.
How You Operate
Redeployable and self-directed: you take ambiguous requirements and drive them forward andyou stay productive when assignments change from one sprint to the next.
Full-lifecycle owner: you care about data quality as a product not just a pipeline and you seeyour work through to production and operational handoff.
You learn the business: you actively pick up the domain (real estate property managementinvestment and financial data) so your models reflect how the business works not just the shapeof the source tables.
You document and share: you write things down and spread knowledge rather than holding it astribal knowledge so others can pick up where you left off.
You ship polished production-grade work. It runs is not the bar; reliability and quality are.
Scope-disciplined and collaborative: you solve the problem in front of you without overengineering and you operate as one team across engineering product analytics and business.
Domain Knowledge (Preferred)
Experience in real estate property management financial services or asset management is astrong plus.
Familiarity with multi-source data environments where data arrives in heterogeneous formatswith varying quality.
Experience building data products that serve multiple business units with different access andgovernance requirements.
Mindset
AI-first mindset: you leverage AI tools in your own workflow and think about how datainfrastructure should evolve as AI capabilities advance. Well want to see something you built onthe side as a passion project.
Clear communicator who can explain data architecture decisions to product managers analystsand business stakeholders.
Tools & Technologies
Databricks Spark Delta Lake Unity Catalog (domains metric views).
Python SQL dbt or similar transformation frameworks.
Postgres and other relational back ends.
Azure cloud services (ADLS Azure ML Synapse) or equivalent; exposure to Azure Web Appsand API layers a plus.
Git CI/CD infrastructure as code (Terraform or similar).
Data catalog lineage and observability tools (Monte Carlo Great Expectations or similar).
MCP RAG frameworks and LLM-powered analytics a plus

The salary range for this position is $115000 - $135000 USD Annually.

Additional Compensation:

Many factors go into determining employee pay within the posted range including business requirements prior experience current skills and geographical location.

• Corporate Positions:Inaddition to the base salary this role may be eligible to participateina quarterly or annual bonus program based onindividual and company performance.
• Onsite Property Positions:Inaddition to the base salary this role may be eligible to participatein weekly monthly and/or quarterly bonus programs.

Robust Benefits Offered*:

• Competitive Medical Dental Vision and Disability & Lifeinsurance benefits. Low (free basic) employee Medical costs for employee-only coverage; costs discounted after 3 and 5 years of service.
• Generous Paid Time off. All new hires start with 15 days of vacation 4 personal days 10 sick days and 11 paid holidays. Plus your birthday off after 1 year of service! Additional vacation accrued with tenure.
• For onsite team members onsite housing discount at Greystar-managed communities are available subject to discount and unit availability.
• 6-Week Paid Sabbatical after 10 years of service (and every 5 years thereafter).
• 401(k) with Company Match up to 6% of pay after 6 months of service.
• Paid Parental Leave and lifetime Fertility Benefit reimbursement up to $10000 (includes adoption or surrogacy).
• Employee Assistance Program.
• Critical Illness Accident HospitalIndemnity PetInsurance and Legal Plans.
• Charitable giving program and benefits.

*Benefits offered for full-time employees. For Union and Prevailing Wage roles compensation and benefits may vary from the listedinformation above due to Collective Bargaining Agreements and/or local governing authority.

Greystar will consider for employment qualified applicants with arrest and conviction records.

Greystar is an equal opportunity employer and does not discriminate in employment on the basis of race color religion sex (including pregnancy sexual orientation and gender identity) national origin age disability genetic information military or veteran status or any other characteristic protected by applicable law.

This position may be performed remotely anywhere within the United States except the state of Alaska.

Important Notice: Greystar will never request your banking details or other sensitive personal information during the interview process. Greystar does not conduct any interviews via text or messaging and all communication will come from official Greystar email addresses (@). If you receive suspicious requests please report them immediately to

ANTICIPATED CLOSING DATE

October 19 2026

This date may be subject to change due to evolving business needs.