More jobs:
Data Platform Engineer
Job in
Scottsdale, Maricopa County, Arizona, 85261, USA
Listed on 2026-07-25
Listing for:
Arkhya Tech. Inc.
Seasonal/Temporary
position Listed on 2026-07-25
Job specializations:
-
IT/Tech
Cloud Computing: Infrastructure & Operations, Data Engineering, IT Infrastructure, SRE/Site Reliability
Job Description & How to Apply Below
Location :
Scottsdale, AZ (100% Onsite)
Type:
Contract
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 work spaces, 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 Dev Ops 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
- 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)
- Expertise in Terraform (mandatory) for infrastructure provisioning
- Proficiency in Ansible for configuration management and automation
- Experience with CI/CD pipelines for infrastructure deployments
- Spark performance tuning and cluster optimization
- Knowledge of containerization (Docker/Kubernetes) is a plus
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