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Platform Infrastructure Engineer

E-Solutions

RemoteFull timeMid levelPosted today
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About the role

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

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