{"id":1156596,"url":"https://alion.io/job/greystar-sr-data-engineer-2","title":"Sr Data Engineer","company":{"id":4551,"name":"Greystar","domain":"greystar.com","url":"https://alion.io/company/greystar","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":84,"open_postings":117,"ghost_share":0,"stale_share":0.615,"repost_share":0.009,"time_to_fill_p50_days":22,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":115000,"max_usd":208000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":340},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Dagster","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Great Expectations","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Scale AI","optional":false},{"name":"Self-Healing","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Tool Use","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-09-21T00:00:00Z","employer_posted_date":"2026-09-21","last_verified_at":"2026-10-17T09:24:08Z","board_verified":true,"closed_at":null,"days_open":26,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":26},"description":"ABOUT GREYSTAR\nGreystar 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 www.greystar.com.\nJOB DESCRIPTION SUMMARY\nJOB DESCRIPTION SUMMARYGreystar'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.We hire for Greystar, not for a single team. You'll 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 you're 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 unlistedYouTube video.Please embed this link at the top of your resume. Applications with a video link will be prioritized\nJOB DESCRIPTION\nJOB DESCRIPTION\nGreystar is building the data foundation that will power the most AI-advanced operator in global multifamily real estate. We're seeking a Senior 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.\nThis 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 \nserve every business unit. Our team includes engineers, designers, and product leaders with experience from Google, Microsoft, Airbnb, Strava, Amazon, and more.\nYou won't be boxed into one standing domain. Once you're assigned, you'll take a project from ingestion through certified “gold” data and into production, hand it cleanly to operations, and then move to the next. Some initiatives will play to a deep specialty; others will ask you to learn a new part of the business fast. Comfort with that kind of movement is part of the job.\nWhat You'll Do\nOwn Initiatives End to End\nTake assigned initiatives from raw ingestion through bronze, silver, and certified gold, staying with the work through deployment and handoff to operations.\nRedeploy across projects as priorities shift, ramping quickly on unfamiliar source systems and business domains.\nDefault to doing it right; when speed is genuinely required, ship a usable solution with a documented path back to the governed, gold standard.\nBuild and Scale AI-Ready Data Infrastructure\nDesign, build, and maintain scalable and self-healing 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).\nDevelop and operate our Data Marketplace (DMP) on Databricks, ensuring data is governed, validated, maintains high data quality, and available for AI/ML workloads.\nBuild data models with real rigor: correct grain, natural and foreign keys, and referential integrity, so downstream AI tools (like MCP) and Data Catalog applications can navigate relationships reliably. \nBuild models optimized for both analytical queries and AI consumption, including feature stores, embedding pipelines, and real-time serving layers.\nImplement data quality frameworks including automated testing, lineage tracking, anomaly detection, and regression testing for critical data assets. Enable AI and MCP Integrations\nBuild and maintain MCP (Model Context Protocol) server integrations that expose Greystar's data to LLM-powered tools and AI agents across the organization.\nDesign APIs and data interfaces that let AI products (GPS, Greystar.com, internal tools) query and act on data in real time. Exposure to full-stack or application development, for example Azure Web Apps built to scale to thousands of users, is a strong plus.\nPartner with Data Science and Product teams to operationalize ML models, building the infrastructure for training, evaluation, deployment, and monitoring.\nEvaluate and integrate AI-powered data tooling (AI-assisted cataloging, automated schema detection, intelligent data quality monitoring).\nCollaborate 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.\nDrive Data Governance and Trust\nImplement and enforce data governance policies including access controls, PII handling, data classification, and compliance requirements across global operations.\nBuild observability into data systems: monitoring, alerting, SLA tracking, and data freshness guarantees.\nContribute to Greystar's AI governance framework, ensuring data used by AI systems is accurate, compliant, and appropriately scoped.\nDocument data models, pipeline architectures, and integration patterns so the work is reusable and the next engineer, or a business-unit analytics team, can self-serve. We treat documentation as part of delivery, not an afterthought.\nWhat You Bring\nData Engineering Excellence\n5+ years of professional data engineering experience building and operating production data platforms.\nDeep expertise with Databricks, Spark, or similar distributed data processing frameworks.\nStrong SQL skills and data modeling experience across analytical (star schema, data vault) and AI/ML workloads, with a firm grasp of keys, grain, referential integrity, data quality, and what it takes to certify a “gold” data asset.\nDeep experience with AI coding tools like Cursor, Codex, Claude Code, etc.\nProficiency in Python; experience with orchestration tools (Airflow, Dagster, or Databricks Workflows).\nExperience with cloud data platforms (ADLS, Synapse, Azure ML; AWS/GCP acceptable) and relational back ends such as Postgres.\nAI/ML Data Infrastructure\nExperience building data infrastructure that supports ML workflows: feature stores, training pipelines, embedding generation, and model serving.\nFamiliarity with LLM integration patterns including RAG architectures, vector databases (Pinecone, Weaviate, or similar), and MCP or tool-use frameworks.\nUnderstanding of how AI/ML models consume data and the engineering requirements for reliable, low-latency AI data serving.\nAwareness of AI governance considerations: data provenance, bias detection, and responsible AI data practices. How You Operate\nRedeployable and self-directed: you take ambiguous requirements and drive them forward, and you stay productive when assignments change from one sprint to the next.\nFull-lifecycle owner: you care about data quality as a product, not just a pipeline, and you see your work through to production and operational handoff.\nYou learn the business: you actively pick up the domain (real estate, property management, investment, and financial data) so your models reflect how the business works, not just the shape of the source tables.\nYou document and share: you write things down and spread knowledge rather than holding it as tribal knowledge, so others can pick up where you left off.\nYou ship polished, production-grade work. “It runs” is not the bar; reliability and quality are.\nScope-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)\nExperience in real estate, property management, financial services, or asset management is a strong plus.\nFamiliarity with multi-source data environments where data arrives in heterogeneous formats with varying quality.\nExperience building data products that serve multiple business units with different access and governance requirements. Mindset\nAI-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.\nClear communicator who can explain data architecture decisions to product managers, analysts, and business stakeholders. Tools & Technologies\nDatabricks, Spark, Delta Lake, Unity Catalog (domains, metric views).\nPython, SQL, dbt or similar transformation frameworks.\nPostgres and other relational back ends.\nAzure cloud services (ADLS, Azure ML, Synapse) or equivalent; exposure to Azure Web Apps and API layers a plus.\nGit, CI/CD, infrastructure as code (Terraform or similar).\nData catalog, lineage, and observability tools (Monte Carlo, Great Expectations, or similar).\nMCP , RAG frameworks, and LLM-powered analytics a plus\nAdditional Compensation:\nMany factors go into determining employee pay within the posted range including business requirements, prior experience, current skills and geographical location.\nCorporate 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.\nOnsite Property Positions: In addition to the base salary, this role may be eligible to participate in weekly, monthly, and/or quarterly bonus programs.\nRobust Benefits Offered*:\nCompetitive 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.\nGenerous 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.\nFor onsite team members, onsite housing discount at Greystar-managed communities are available subject to discount and unit availability.\n6-Week Paid Sabbatical after 10 years of service (and every 5 years thereafter).\n401(k) with Company Match up to 6% of pay after 6 months of service.\nPaid Parental Leave and lifetime Fertility Benefit reimbursement up to $10,000 (includes adoption or surrogacy).\nEmployee Assistance Program.\nCritical Illness, Accident, Hospital Indemnity, Pet Insurance and Legal Plans.\nCharitable giving program and benefits.\n*Benefits offered for full-time employees. For Union and Prevailing Wage roles, compensation and...","description_format":"text","description_chars":12928,"description_truncated":true,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Life insurance","Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Real Estate","Residential Real Estate","Property Management"],"lifecycle":[{"event":"open","at":"2026-09-23T21:49:08Z"}],"visa":[],"liveness":{"score":29,"band":"fade","label":"Fading","p_open":1,"p_active":0.521,"p_room":0.55,"age_days":26,"expected_fill_days":22,"reasons":["conf:0","stale_co","velocity","win:tail","comp:brand"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/greystar-sr-data-engineer-2","json_url":"https://alion.io/job/greystar-sr-data-engineer-2.json","meta":{"generated_at":"2026-10-17T20:58:01Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":5327,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4551},"rest":"https://alion.io/mcp/rest/get_company?id=4551"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fgreystar-sr-data-engineer-2"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fgreystar-sr-data-engineer-2"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fgreystar-sr-data-engineer-2"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/greystar-sr-data-engineer-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fgreystar-sr-data-engineer-2"}]}