Senior Azure Databricks Engineer

Onsite Flexibility: Hybrid — 3 days onsite per week

• Position Type: Contract
• Contract Duration: 12 months
• Pay Rate: $51.40–$66.71 / Hour (USD)
• Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Location: Glendale, AZ

• Position Type: Contract
• Contract Duration: 12 months
• Pay Rate: $51.40–$66.71 / Hour (USD)
• Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

This role is for a Senior Azure Databricks Engineer based in Glendale, AZ, with 8 to 10 years of experience required. The engineer will collaborate with Data Platforms and Integration teams to architect and implement scalable enterprise data platform solutions.

• Collaborate with Data Platforms and Integration team in architecting and implementing scalable enterprise data platform solutions utilizing Azure Databricks
  , Delta Lake, Unity Catalog, Azure Data Lake Storage Gen2, and related Azure services.
• Design and develop enterprise data engineering frameworks supporting batch, streaming, ELT/ETL, and real-time analytics workloads.
• Administer and maintain Azure Databricks work spaces including cluster configuration, job scheduling, workspace administration, Unity Catalog implementation, secret management, compute policies, cluster policies, and workspace governance.
• Define and implement enterprise security architecture including identity integration with Microsoft Entra  (Azure AD), Role-Based Access Control (RBAC), Privileged Identity Management (PIM), data encryption, private networking, managed identities, Key Vault integration, and secure access patterns.
• Establish enterprise data governance standards utilizing Unity Catalog including data lineage, data quality, metadata management, catalog organization, access policies, and audit capabilities.
• Optimize Databricks workloads through performance tuning, Spark optimization, cluster sizing, workload isolation, caching strategies, partitioning, Delta optimization, Photon, and cost optimization best practices.
• Design enterprise monitoring, logging, operational dashboards, alerting, and platform health monitoring utilizing Azure Monitor, Log Analytics, Application Insights, and Databricks system tables.
• Develop reusable architecture patterns, reference implementations, development standards, naming conventions, coding standards, operational procedures, and platform documentation.
• Support migration of legacy enterprise data warehouses, ETL solutions, and reporting platforms to Azure Databricks and modern Lakehouse architecture.
• Provide technical support and troubleshooting for production incidents related to Azure Databricks, Spark workloads, data pipelines, and platform infrastructure.

• At least 8–10 years of experience in designing and implementing enterprise data platforms.
• At least 5 years of hands‑on Azure Databricks experience in enterprise environments.

• Experience with architecting modern Lakehouse solutions using Azure Databricks and Delta Lake.
• Experience in administering Azure Databricks work spaces, clusters, Unity Catalog, compute policies, job orchestration, and workspace security.
• Experience in developing data engineering solutions using Apache Spark (PySpark and/or Spark SQL).
• Experience in implementing enterprise data governance utilizing Unity Catalog, metadata management, data lineage, and fine‑grained access controls.
• Experience designing and working with enterprise security architectures including RBAC, Managed Identities, Private Endpoints, Key…