Databricks Platform Engineer

We are seeking a highly skilled Databricks Platform Engineer to join existing engineering team. This role is focused on designing, optimizing, and maintaining the Databricks platform and architecture, enabling development teams to efficiently build and deploy data solutions. The ideal candidate will act as a platform expert, ensuring scalability, reliability, governance, and performance of the Databricks ecosystem while supporting developers with best practices, tools, and frameworks., Platform Engineering & Architecture

• Design, implement, and maintain Databricks platform architecture to support enterprise-scale data workloads
• Establish best practices for workspace setup, cluster management, and job orchestration
• Optimize platform performance, scalability, and cost efficiency
• Define and enforce standards for data engineering and analytics workloads within Databricks

Developer Enablement

• Support development teams by providing guidance, documentation, and reusable frameworks
• Enable developers with CI/CD pipelines, automation, and deployment standards
• Troubleshoot and resolve platform-related issues impacting development teams
• Provide technical mentorship and onboarding support to engineers using Databricks

Governance, Security & Compliance

• Implement and manage data governance, access controls, and security models (Unity Catalog, RBAC, etc.)
• Ensure compliance with enterprise data policies and regulatory requirements
• Monitor and audit platform usage, access patterns, and data lineage

Integration & Ecosystem Management

• Integrate Databricks with cloud platforms (AWS/Azure/Google Cloud Platform), data lakes, and enterprise systems
• Manage connectivity with tools such as Power BI, APIs, data ingestion frameworks, and orchestration tools
• Support ingestion and processing frameworks (e.g., batch, streaming, Delta Lake)

Operational Excellence

• Monitor platform health, performance, and usage metrics
• Implement automation for provisioning, monitoring, and scaling
• Drive continuous improvements in platform reliability and developer experience

• Bachelor s degree in Computer Science, Engineering, or related field (or equivalent experience)
• 5+ years of experience in data engineering or platform engineering roles
• 3+ years of hands-on experience with Databricks (architecture, administration, or platform engineering)
• Strong understanding of distributed data processing (Spark)
• Experience with cloud platforms (Azure preferred, or AWS/Google Cloud Platform)
• Knowledge of data lake architecture, Delta Lake, and modern data platforms
• Experience implementing security, governance, and access control frameworks
• Familiarity with CI/CD pipelines, DevOps practices, and infrastructure as code (Terraform, etc.)