Backend AI-Forward Data 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 $300 billion of real estate in more than 265 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 $35 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 www.greystar.com . JOB DESCRIPTION SUMMARY Greystar’s 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. In addition to your resume, all candidates are required to 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 without a video link will not be reviewed. JOB DESCRIPTION About the Role Greystar is building the data foundation that will power the most AI-advanced operator in global multifamily real estate. We’re seeking a Backend AI-Forward Data Engineer to design, build, and operate the core data infrastructure that enables AI-powered products, analytics, and decision-making across a multi-billion dollar global portfolio. This role sits at the intersection of data engineering and applied AI — you’ll build the pipelines, platforms, and interfaces that make Greystar’s proprietary data accessible, trustworthy, and AI-ready. You will work across 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 experience from Google, Microsoft, Airbnb, Strava, Amazon, and more. What You’ll Do Build and Scale AI-Ready Data Infrastructure Design, build, and maintain scalable data pipelines that ingest, transform, and serve data from dozens of source systems (PMS, CRM, financial systems, IoT, web/mobile analytics, and third-party providers). Develop and operate our Data Management Platform (DMP) on Databricks, ensuring data is governed, validated, and available for AI/ML workloads. Build data models optimized for both analytical queries and AI consumption — including feature stores, embedding pipelines, and real-time serving layers. Implement data quality frameworks including automated testing, lineage tracking, anomaly detection, and regression testing for critical data assets. Enable AI and MCP Integrations Build and maintain MCP (Model Context Protocol) server integrations that expose Greystar’s data to LLM-powered tools and AI agents across the organization. Design APIs and data interfaces that allow AI products (GPS, Greystar.com, internal tools) to query and act on data in real time. Partner with Data Science and Product teams to operationalize ML models — building the infrastructure for model training, evaluation, deployment, and monitoring. Evaluate and integrate AI-powered data tooling (e.g., AI-assisted data cataloging, automated schema detection, intelligent data quality monitoring). Collaborate with other engineers on AI integration patterns, prompt engineering, and modern development practices. We are an AI forward team and it’s moving fast so we test, iterate, share and repeat. Drive Data Governance and Trust Implement and enforce data governance policies including access controls, PII handling, data classification, and compliance requirements across global operations. Build observability into data systems: monitoring, alerting, SLA tracking, and data freshness guarantees. Contribute to Greystar’s AI governance framework, ensuring data used by AI systems is accurate, compliant, and appropriately scoped. Document data models, pipeline architectures, and integration patterns to enable self-service for business unit analytics teams. What You Bring Data Engineering Excellence 5+ years of professional data engineering experience building and operating production data platforms. Deep expertise with Databricks, Spark, or similar distributed data processing frameworks. Strong SQL skills and experience with data modeling for both analytical (star schema, data vault) and AI/ML workloads. Deep experience with AI coding tools like Cursor, Codex, Claude Code, etc. Proficiency in Python; experience with orchestration tools (Airflow, Dagster, or Databricks Workflows). Experience with cloud data platforms (ADLS, Synapse, Azure ML; AWS/GCP acceptable). AI/ML Data Infrastructure Experience building data infrastructure that supports ML workflows: feature stores, training pipelines, 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 for reliable, low-latency AI data serving. Awareness of AI governance considerations: data provenance, bias detection, and responsible AI data practices. Domain Knowledge (Preferred) Experience in real estate, property management, financial services, or asset management is a strong plus. Familiarity with multi-source data environments where data arrives in heterogeneous formats with varying quality. Experience building data products that serve multiple business units with different access and governance requirements. Mindset & Communication AI-first mindset — you leverage AI tools in your own workflow and think about how data infrastructure should evolve as AI capabilities advance . We’ll want to see something you built on the side as a passion project. Strong ownership mentality; you care about data quality as a product, not just a pipeline. Clear communicator; able to explain data architecture decisions to product managers, analysts, and business stakeholders. Collaborative approach across engineering, product, analytics, and business teams. Tools & Technologies Databricks, Spark, Delta Lake, Unity Catalog. Python, SQL, dbt or similar transformation frameworks. Azure cloud services (ADLS, Azure ML, Synapse) or equivalent. Git, CI/CD, infrastructure as code (Terraform or similar). Familiarity with data catalog, lineage, and observability tools (Monte Carlo, Great Expectations, or similar). #LI-Remote #LI-BB1 The salary range for this position is $100,000-$125,000 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 : In addition to the base salary, this role may be eligible to participate in a quarterly or annual bonus program based on individual and company performance. Onsite Property Positions : In addition to the base salary, this role may be eligible to participate in weekly, monthly, and/or quarterly bonus programs. Robust Benefits Offered*: Competitive Medical, Dental, Vision, and Disability & Life insurance 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 $10,000 (includes adoption or surrogacy). Employee Assistance Program. Critical Illness, Accident, Hospital Indemnity, Pet Insurance 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 listed information 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 (@greystar.com). If you receive suspicious requests, please report them immediately to [email protected]. ANTICIPATED CLOSING DATE September 21, 2026 This date may be subject to change due to evolving business needs.