Data Platform Engineer

Greystar is a leading global real estate platform specializing in property management and investment services. They are seeking a Data Platform Engineer to oversee the reliability and efficiency of their enterprise data infrastructure, primarily focusing on Databricks and Microsoft Azure, while collaborating with various teams to optimize data operations.

Responsibilities:

• 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 DataOps 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 GitHub 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
• Manage Azure Active Directory (AAD) service principals, RBAC 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 Dev, Staging, and Production Databricks environments — cluster policies, Unity Catalog hierarchy, access controls, and compute configurations
• Define and enforce environment promotion hygiene: configuration drift detection, environment-specific secret management, and pre-production validation gates
• Maintain infrastructure-as-code (IaC) scripts and configuration templates to ensure reproducible, auditable environment provisioning across all tiers
• Produce thorough technical documentation: runbooks, deployment playbooks, incident post-mortems, ADRs, and platform specs
• 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 LLMs and ML 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 — automated retry logic, circuit breakers, and remediation triggers — as production-grade platform features, not experiments
• 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, leading near-term delivery of platform-level self-healing and proactive alerting capabilities
• Own DMP pipeline architecture patterns from an infrastructure standpoint — Delta Live Tables (DLT) 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 (VACUUM, OPTIMIZE)
• Partner with analytics engineers to ensure pipeline designs conform to platform infrastructure standards, SLA tiers, and compute budget constraints
• Design and maintain DR strategies for the DMP platform — including Delta table backup policies, ADLS Gen2 geo-redundancy configuration, and Databricks workspace recovery runbooks
• Define RTO and RPO targets for business-critical DMP data domains; 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

Requirements:

• 5+ years of platform engineering, infrastructure engineering, or data operations experience in a production environment
• Expert-level Databricks administration: Unity Catalog, cluster policies, workspace management, compute configuration, and Delta Lake internals
• Strong command of the Azure data services ecosystem: ADLS Gen2, ADF, Azure Monitor, Log Analytics, Key Vault, Cost Management, and Event Hub
• Identity and access management: Azure Active Directory, service principals, RBAC, and Unity Catalog governance policies
• Hands-on experience with ADF pipeline design and orchestration at scale
• Spark performance tuning: partitioning, Z-ordering, compute spend optimization, and bottleneck profiling
• Proven CI/CD experience using GitHub Enterprise: environment promotion, rollback, and release management for data pipelines
• Python and/or SQL for automation scripts, compliance validation, and platform tooling
• Knowledge of medallion / lakehouse architecture patterns and multi-environment deployment discipline
• Terraform / Infrastructure-as-Code (IaC): provisioning and managing Databricks workspaces, Azure resources, Unity Catalog configurations, and environment-specific infrastructure through version-controlled IaC
• Azure DevOps Pipelines: build and release pipeline configuration, YAML pipeline authoring, and integration with GitHub Enterprise for end-to-end deployment automation
• Azure networking: VNet configuration, private endpoints for Databricks and ADLS Gen2, NSG rules, firewall policies, and DNS resolution for secure data platform connectivity
• Azure Monitor & Log Analytics: KQL query authoring, alert rule configuration, diagnostic settings, workbook creation, and cluster event monitoring for proactive platform health management
• Delta Lake internals: VACUUM, OPTIMIZE, ZORDER, time travel, table statistics, and transaction log management for production-grade Delta table lifecycle governance
• 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: Yardi, Entrata, or RealPage in multi-tenant environments
• Background in legacy BI migration or platform modernization programs
• Linear for engineering sprint and release management