Data Platform Engineer R0196880 Remote United States Full time

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 seeking a Platform Engineer to join the Data team. This is a senior, deeply technical platform operations role responsible for the reliability, governance, and cost efficiency of Greystar’s enterprise data infrastructure — a Databricks-native medallion architecture (Bronze → Silver → Gold) running entirely on Microsoft Azure. You will work within the Data Ops pod under the Analytics Engineering umbrella, owning Databricks workspace administration, Unity Catalog governance, Azure infrastructure operations, and multi-system platform support.

This role is platform-engineering-heavy. Most of your day lives inside Databricks workspace administration and the full Azure data services stack: ADLS Gen2, Azure Data Factory, Azure Monitor, Key Vault, Log Analytics, and beyond. You will enforce platform standards, govern identity and access, optimize compute and storage spend, and provide platform support for EDP, DALDW, ADF, Synapse, Cosmos DB, and SQL Server.

Deep mastery of Databricks administration and the Azure platform is a baseline expectation.

• Own Databricks workspace administration: upgrades, cluster policies, compute configurations, and Delta table lifecycle management
• Administer Unity Catalog: access controls, service principal (SP), group, and user provisioning, governance policies, and data lineage
• Tune Spark jobs for performance, reliability, and cost — profiling bottlenecks, optimizing partitioning, managing Z-ordering, and controlling compute spend
• Architect and enforce DMP platform standards: naming conventions, schema evolution policies, SLA tiers, and medallion layer contracts
• Leverage Databricks Mosaic AI and Genie to build AI-native Data Ops capabilities including intelligent pipeline monitoring and anomaly detection

• Operate the full Azure data services stack: ADLS Gen2, Azure Data Factory (ADF), 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 various systems and platforms including access management, storage optimization, and compliance
• Support additional platforms including ADF, Synapse Analytics, Cosmos DB, and Azure SQL Server
• Manage storage allocation, cluster optimization, and resource provisioning across all supported platforms
• Support compliance, audit readiness, and 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 Git Hub Enterprise: branch strategies, PR automation, environment-specific configuration management, and release gating
• Enforce deployment standards: automated testing gates, rollback procedures, change documentation, and environment parity controls
• Use Linear for sprint planning, release tracking, and issue management across deployment cycles