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Greystar Worldwide

Vertical-integrated residential rental housing platform

Data Platform Engineer

Platform EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA$125k - $150k /yr

About the Job

Requirements

  • At least 5 years of platform engineering, infrastructure engineering, or data operations experience in a production environment.
  • Expert-level Databricks administration, including Unity Catalog, cluster policies, workspace management, compute configuration, and Delta Lake internals.
  • Strong command of the Azure data services ecosystem, including ADLS Gen2, Azure Data Factory, Azure Monitor, Log Analytics, Key Vault, Cost Management, and Event Hub.
  • Identity and access management experience with Azure Active Directory, service principals, role-based access control, and Unity Catalog governance policies.
  • Hands-on experience with Azure Data Factory pipeline design and orchestration at scale.
  • Spark performance tuning experience, including partitioning, Z-ordering, compute-spend optimization, and bottleneck profiling.
  • Proven CI/CD experience using GitHub Enterprise, including environment promotion, rollback, and release management for data pipelines.
  • Python and/or SQL skills for automation scripts, compliance validation, and platform tooling.
  • Knowledge of medallion or lakehouse architecture patterns and multi-environment deployment discipline.
  • Terraform or infrastructure-as-code experience provisioning and managing Databricks workspaces, Azure resources, Unity Catalog configurations, and environment-specific infrastructure through version-controlled code.
  • Azure DevOps Pipelines experience, including build and release pipeline configuration, YAML pipeline authoring, and integration with GitHub Enterprise for end-to-end deployment automation.
  • Azure networking experience, including virtual network configuration, private endpoints for Databricks and ADLS Gen2, network security group rules, firewall policies, and DNS resolution for secure data platform connectivity.
  • Azure Monitor and Log Analytics experience, including KQL query authoring, alert rule configuration, diagnostic settings, workbook creation, and cluster event monitoring for proactive platform health management.
  • Delta Lake internals knowledge, including VACUUM, OPTIMIZE, ZORDER, time travel, table statistics, and transaction log management for production-grade Delta table lifecycle governance.
  • Participate in on-call rotation coverage across the assigned shift window.
  • Manage ServiceNow and Asana ticket queues according to team SLA commitments.
  • Track and close Linear and DevOps work items as part of sprint cycles.
  • Contribute to the team knowledge base, runbook library, and post-incident documentation.

Responsibilities

  • Own Databricks workspace administration, including upgrades, cluster policies, compute configurations, and Delta table lifecycle management.
  • Administer Unity Catalog access controls, service principal, group, and user provisioning, governance policies, and data lineage.
  • Tune Spark jobs for performance, reliability, and cost by profiling bottlenecks, optimizing partitioning, managing Z-ordering, and controlling compute spend.
  • Architect and enforce DMP platform standards, including naming conventions, schema evolution policies, SLA tiers, and medallion layer contracts.
  • Use Databricks Mosaic AI and Genie to build AI-native DataOps capabilities, including intelligent pipeline monitoring and anomaly detection.
  • Operate the Azure data services stack, including ADLS Gen2, Azure Data Factory, Azure Monitor, Log Analytics, Key Vault, and Event Hub.
  • Collaborate with Azure infrastructure and cloud engineering teams on networking, identity, security, and resource provisioning.
  • Drive cost governance through Azure Cost Management, Databricks DBU optimization, and storage lifecycle policies.
  • Provide platform support for supported systems and platforms, including access management, storage optimization, and compliance.
  • Support ADF, Synapse Analytics, Cosmos DB, and Azure SQL Server.
  • Manage storage allocation, cluster optimization, and resource provisioning across supported platforms.
  • Support compliance and audit readiness, and manage Key Vault secret rotation and management.
  • Own the full deployment pipeline for DMP data workflows, promoting changes from development through staging to production.
  • Build and maintain CI/CD workflows using GitHub Enterprise, including branch strategies, pull request automation, environment-specific configuration management, and release gating.
  • Enforce deployment standards, including automated testing gates, rollback procedures, change documentation, and environment parity controls.
  • Use Linear for sprint planning, release tracking, and issue management across deployment cycles.
  • Manage Azure Active Directory service principals, role-based access control assignments, and Unity Catalog permission policies.
  • Partner with the Data Governance team to enforce data contracts, ownership standards, and quality SLAs within Unity Catalog.
  • Maintain data lineage, metadata management, and governance framework documentation.
  • Ensure platform configurations meet security, compliance, and audit requirements.
  • Own workspace configuration parity across development, staging, and production Databricks environments, including cluster policies, Unity Catalog hierarchy, access controls, and compute configurations.
  • Define and enforce environment promotion practices, including configuration drift detection, environment-specific secret management, and pre-production validation gates.
  • Maintain infrastructure-as-code scripts and configuration templates for reproducible, auditable environment provisioning across all tiers.
  • Produce technical documentation, including runbooks, deployment playbooks, incident post-mortems, architecture decision records, and platform specifications.
  • Partner with analytics engineers, data governance, and product stakeholders on platform design and capacity planning.
  • Participate in on-call rotation and support SLA commitments for business-critical DMP data domains.
  • Build and maintain AI-powered platform observability infrastructure using large language models and machine learning models to detect pipeline drift, classify anomalies, predict SLA risk, and generate automated incident summaries at the platform layer.
  • Architect and deploy self-healing pipeline capabilities, including automated retry logic, circuit breakers, and remediation triggers, as production-grade platform features.
  • Integrate Databricks Mosaic AI and Genie into operational platform workflows for intelligent cluster management, anomaly detection, and natural-language platform diagnostics.
  • Contribute to Greystar’s 18-month agentic AI roadmap by leading near-term delivery of platform-level self-healing and proactive alerting capabilities.
  • Own DMP pipeline architecture patterns from an infrastructure standpoint, including Delta Live Tables design standards, schema evolution enforcement, and medallion layer contracts.
  • Define and enforce platform-wide naming conventions, partitioning strategies, Z-ordering policies, and Delta table optimization schedules, including VACUUM and OPTIMIZE.
  • Partner with analytics engineers to ensure pipeline designs conform to platform infrastructure standards, SLA tiers, and compute budget constraints.
  • Design and maintain disaster-recovery strategies for the DMP platform, including Delta table backup policies, ADLS Gen2 geo-redundancy configuration, and Databricks workspace recovery runbooks.
  • Define recovery time and recovery point objectives for business-critical DMP data domains, and test and validate recovery procedures on a recurring basis.
  • Maintain business continuity plans aligned with Azure region failover capabilities and Greystar’s enterprise SLA commitments.

Desired Qualifications

  • Experience with Synapse Analytics, Cosmos DB, or Azure SQL Server in production data environments.
  • Familiarity with Databricks Mosaic AI, Genie, or AI-native platform observability capabilities.
  • Background in data lineage tooling, metadata management, and Unity Catalog governance frameworks.
  • Experience with ERP system integrations, including Yardi, Entrata, or RealPage, in multi-tenant environments.
  • Background in legacy BI migration or platform modernization programs.
  • Experience using Linear for engineering sprint and release management.

About the Company

Greystar Worldwide

Vertical-integrated residential rental housing platform

Greystar Worldwide focuses on residential rental housing with a vertically integrated model that combines investment, development, and property management. Its products work by owning and operating rental properties across international, regional, and local markets through a global platform and local offices, enabling scale, professional reporting, and capital relationships while maintaining local execution. The company differentiates itself through its full-stack approach, combining ownership, development, management, and investment disciplines, plus a large global workforce and long industry experience to provide consistent service and value across all phases of the real estate cycle. Its goal is to create high-quality, inviting homes and enhanced living experiences by leveraging its integrated capabilities and extensive network of capital and expertise.

Company size
10,001+
Company stage
Debt Financing
Total funding
$511.6M
Headquarters
Charleston, SC
Founded
1993

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