Platform Engineer( On-Premises)

Job Summary

Key Responsibilities

• Install, configure, deploy, and maintain data platform components in on-premises environments.
• Perform day-to-day Data Platform Administration, monitoring, maintenance, upgrades, and operational support.
• Deploy and support data platform components running on VMware-based infrastructure.
• Integrate platform configurations and deployment processes with Git-based version control.
• Integrate data platforms with enterprise security solutions, including IAM and PAM.
• Support platform deployment and operations across Development, QA, and Production environments.
• Monitor platform availability, performance, capacity, resource utilization, and overall platform health.
• Troubleshoot and resolve platform, infrastructure, deployment, configuration, storage, network, and integration issues.
• Support containerized platform components using Docker and/or Kubernetes, where applicable.
• Collaborate with Data Engineering, Infrastructure, DevOps, Security, Network, and Application teams to maintain a stable, secure, and highly available data platform.

Must-Have Skills

Good-to-Have Skills

Qualifications

• 3–5 Years
• Job Title: Data Platform Engineer
• Employment Type: Full-Time
• Work Mode: On-site / Hybrid, based on project requirements
• Education: Bachelor’s Degree in Computer Science or a related field
• Engagement Duration: 3–5 Months
• Environment: On-Premises | Dev, QA & Production
• Job Summary
• We are looking for a hands-on Data Platform Engineer with strong experience in the installation, configuration, administration, and support of data platform components in on-premises environments.
• The role requires experience with platform administration, VMware-based infrastructure, Git integration, and enterprise security integration involving IAM and PAM. The engineer will be responsible for supporting platform deployment, configuration, maintenance, troubleshooting, and operational activities across Development, QA, and Production environments.
• The ideal candidate should also have a solid understanding of infrastructure, networking, storage, security, and container technologies such as Docker and Kubernetes.
• Key Responsibilities
• Install, configure, deploy, and maintain data platform components in on-premises environments.
• Perform day-to-day Data Platform Administration, monitoring, maintenance, upgrades, and operational support.
• Deploy and support data platform components running on VMware-based infrastructure.
• Integrate platform configurations and deployment processes with Git-based version control.
• Integrate data platforms with enterprise security solutions, including IAM and PAM.
• Support platform deployment and operations across Development, QA, and Production environments.
• Monitor platform availability, performance, capacity, resource utilization, and overall platform health.
• Troubleshoot and resolve platform, infrastructure, deployment, configuration, storage, network, and integration issues.
• Support containerized platform components using Docker and/or Kubernetes, where applicable.
• Collaborate with Data Engineering, Infrastructure, DevOps, Security, Network, and Application teams to maintain a stable, secure, and highly available data platform.
• Must-Have Skills
• 3–5 years of relevant experience in Data Platform Engineering, infrastructure, or Platform Administration.
• Strong hands-on experience with installation and configuration of data platform components in on-premises environments.
• Strong understanding and hands-on experience in Platform Administration.
• Experience working with VMware-based infrastructure.
• Hands-on experience integrating platforms and deployment/configuration processes with Git.
• Experience with enterprise security integrations involving IAM and PAM.
• Good knowledge of platform deployment, configuration, maintenance, upgrades, monitoring, and troubleshooting.
• Experience supporting Development, QA, and Production environments.
• Good understanding of infrastructure, networking, storage, backup/recovery, and security concepts relevant to enterprise data platforms.
• Exposure to Docker and/or Kubernetes for containerized platform deployments.
• Good-to-Have Skills
• Experience with MinIO and Apache Iceberg.
• Experience with Starburst or Dremio.
• Experience with Apache Spark.
• Experience with Informatica.
• Understanding of modern Data Lake and Data Lakehouse architectures.