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