Databricks Platform Engineer

Experience:  3 to 6 years Notice Period:  Immediate to 15 days Location:  Bangalore Work from office JOB DESCRIPTION Job Description: Databricks Platform Engineer / Administrator (AWS) Department: Data Engineering / Cloud Platform / DevOps About the Role We are looking for a skilled and proactive Databricks Platform Engineer / Administrator  to manage, optimize, and govern our Databricks environment on AWS. The ideal candidate will be responsible for overseeing platform operations, optimizing performance and cost, and ensuring secure and efficient use of Databricks and integrated AWS services. This role sits at the intersection of platform engineering, data infrastructure, and cost governance, requiring both technical depth and cross-functional collaboration. Key Responsibilities Platform Administration Deploy, configure, and manage Databricks workspaces  on AWS. Set up and maintain AWS infrastructure  (VPCs, IAM roles, S3, security groups) to support Databricks operations. Manage user access, job permissions, cluster configurations, and workspace-level controls. Cost Optimization Implement and enforce cluster policies  to control resource consumption and prevent cost overruns. Promote efficient compute usage by enabling job clusters , auto-termination , and spot instance  strategies. Monitor and analyze cost using AWS Cost Explorer , Databricks REST APIs , and internal dashboards. Optimize storage costs through S3 lifecycle policies , Delta Lake optimization , and table version management . Performance Tuning Analyze and tune Spark job performance , including partitioning, caching, and join strategies. Provide guidance on using Photon runtime , Delta Live Tables , and SQL optimization best practices . Collaborate with data engineers and analytics teams to improve job execution efficiency and pipeline throughput. Monitoring & Observability Set up and manage logging, monitoring, and alerting  via CloudWatch, Databricks audit logs, and external tools. Track metrics such as cluster utilization, job failures, job durations, and resource bottlenecks. Develop dashboards for real-time visibility into platform usage, performance, and cost. Security & Governance Enforce access control through Unity Catalog , IAM roles , and cluster policies . Ensure compliance with enterprise security policies, data governance standards, and audit requirements. Prevent data duplication and misuse through strong access boundaries and usage monitoring. Automation & Documentation Automate provisioning and configuration using Terraform , Databricks CLI , and REST APIs . Maintain detailed documentation of cluster policies, platform standards, optimization playbooks, and cost governance guidelines. Drive platform standardization and advocate for best practices across teams. Qualifications Required 3–6+ years of experience managing Databricks on AWS  or similar Spark-based platforms. Strong hands-on experience with AWS services  (S3, IAM, VPC, EC2, CloudWatch). Proficiency in Spark performance tuning  and Databricks architecture . Solid understanding of cost optimization strategies  in cloud-based data platforms. Experience with Databricks cluster policies , job scheduling , and Delta Lake . Familiarity with Python, SQL, Terraform , and Databricks REST APIs . Preferred Experience with Unity Catalog , Delta Live Tables , or MLflow . Knowledge of AWS cost governance tools  (Cost Explorer, Budgets, Trusted Advisor). Prior work in FinOps, DataOps, or Cloud Center of Excellence (CCoE) roles. Certifications such as: Databricks Certified Data Engineer / Admin AWS Certified Solutions Architect / DevOps Engineer