Data Platform Infrastructure Engineer

Role : Data Platform Infrastructure Engineer
Location : Scottsdale AZ (100% onsite)
Rate : $65
Indent :
SF_OP_204640-8-2

Preferred Skill Combination (Must-Have Exposure to One or Both):

• Cloudera + Databricks + Terraform + AWS

Role Overview
We are seeking a highly skilled Data Platform Infrastructure Engineer to design, build, and manage scalable data platforms across on-premise and cloud environments. The role involves working with cluster technologies, infrastructure automation, and modern data ecosystems to enable reliable and high-performing data platforms. Key Responsibilities

• Design, deploy, and manage data platform infrastructure across on-prem (Cloudera) and cloud (AWS, Databricks) environments
• Build and maintain distributed data clusters ensuring high availability, scalability, and performance
• Automate infrastructure provisioning using Terraform and Ansible
• Manage and optimize Cloudera Hadoop ecosystems (HDFS, Hive, Spark, YARN, etc.)
• Deploy and manage Databricks workspaces, clusters, and integrations on AWS
• Implement infrastructure-as-code (IaC) and configuration management best practices
• Monitor cluster performance, troubleshoot issues, and ensure system reliability
• Collaborate with data engineers, architects, and DevOps teams to support data pipelines and analytics workloads
• Ensure security, compliance, and governance across data platforms
• Support migration from on-prem to cloud-based data platforms

Technical Skills Required
Core Technologies

• Strong experience in Cloudera (CDH/CDP) cluster setup and administration
• Hands-on experience with Databricks (cluster management, jobs, notebooks)
• Strong exposure to AWS (EC2, S3, IAM, VPC, EMR, networking concepts)

Infrastructure & Automation

• Expertise in Terraform (mandatory) for infrastructure provisioning
• Proficiency in Ansible for configuration management and automation
• Experience with CI/CD pipelines for infrastructure deployments

Cluster & Data Technologies

• Experience managing distributed systems / cluster technologies
• Strong understanding of:
  • Hadoop ecosystem (HDFS, Hive, Spark, Kafka, etc.)
  • Spark performance tuning and cluster optimization
• Knowledge of containerization (Docker/Kubernetes) is a plus