W2 Contract Req: Azure Databricks Administrator (Remote/USA)

Cyberollie; United States; Remote; USD 80,000 - 100,000; Full time

Job summary

An innovative firm is seeking a Mid-Senior Level Cloud Administrator to manage and optimize Azure Databricks workspaces. This role involves deploying, configuring, and maintaining Databricks environments, ensuring compliance with data governance policies, and implementing security measures. The ideal candidate will have strong skills in performance monitoring and automation using Terraform. Join a dynamic team that values collaboration and continuous improvement, where you can make a significant impact on cloud infrastructure and data management practices. This opportunity offers a competitive salary and the flexibility of remote work.

Qualifications

• Experience with Azure Databricks and performance optimization.
• Strong understanding of IAM and data governance policies.

Responsibilities

• Deploy and maintain Azure Databricks workspaces for optimal performance.
• Integrate Databricks with various data sources and automate cluster management.

Skills

Azure Databricks

Terraform

Databricks SQL

CI/CD pipelines

Identity and Access Management (IAM)

Performance Monitoring

Data Governance

Tools

Azure Data Factory

Snowflake

Kafka

GitHub

Azure DevOps

Job description

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Location - Remote / USA

Job Type: Contract / 6 Months Plus

• Deploy, configure, and maintain Azure Databricks workspaces
• Manage clusters, pools, and jobs for optimal performance.
• Handle Databricks Runtime upgrades and compatibility testing.
• Configure Databricks notebooks, Repos, and Delta Lake for efficient workflows.
• Security & Access Control:
• Implement Identity and Access Management (IAM) using Azure AD / Azure IAM / SCIM.
• Set up and enforce Role-Based Access Control (RBAC) and network security.
• Ensure compliance with data governance policies (Unity Catalog, creation of Catalogs, schema etc.).
• Applying grants of catalogs and schemas
• Manage personal access tokens (PATs) and OAuth-based authentication.
• Performance Monitoring & Optimization:
• Monitor cluster performance, auto-scaling, and cost optimization.
• Analyze and fine-tune Spark jobs to improve execution efficiency.
• Use Databricks SQL for querying and performance diagnostics.
• Integration & Automation:
• Integrate Databricks with Azure Data Factory, Synapse, Snowflake, Kafka, and other data sources.
• Automate cluster management using Terraform.
• Implement CI/CD pipelines for Databricks notebooks using GitHub or Azure DevOps.
• Troubleshooting & Support:
• Investigate and resolve job failures, cluster crashes, and query performance issues.
• Provide L2/L3 support for Databricks infrastructure issues.
• Collaborate with Databricks support for bug fixes and escalations

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting

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