DevOps & Data Engineer - GCP (Google Cloud Platform)

NTT DATA Services • Milton, GA

8d • $106,840 - $160,260 • Remote

About The Position

NTT DATA is seeking a DevOps & Data Engineer with expertise in Google Cloud Platform (GCP) to join our team. This role involves developing AI/ML applications, building cloud-native solutions, and managing data pipelines. You will work with cutting-edge technologies like Google's Gemini API, Databricks, and serverless architectures to deliver scalable AI solutions. The position requires a strong understanding of DevOps principles, Infrastructure as Code, and cloud security best practices. You will collaborate with cross-functional teams to ensure the successful delivery of innovative AI solutions.

Requirements

• 5+ years of experience in Backend Development, AI/ML Engineering, DevOps, or Cloud Engineering.
• 5+ years experience with Google Cloud Platform services including Cloud Run, GKE, BigQuery, AlloyDB, Cloud Storage, and serverless technologies.
• 5+ years experience developing applications using Python.
• 5+ years experience with Databricks for AI/ML and data processing workloads.
• 5+ years experience with REST API development and Google Cloud API Gateway.
• 5+ years experience with CI/CD, GitOps, Azure DevOps, and JFrog Artifactory.
• 5+ years Experience implementing Infrastructure as Code using Terraform.
• 5+ years experience with Pub/Sub or Kafka.
• 5+ years experience of GCP IAM, encryption, and cloud security best practices.

Nice To Haves

• Strong analytical, troubleshooting, and problem-solving skills.
• Good communication and collaboration skills.

Responsibilities

• Develop AI/ML applications leveraging Google's Gemini API for natural language understanding and generation.
• Build and enhance cloud-native applications using Python, Databricks, and Google Cloud Platform.
• Design, develop, and maintain scalable backend services using Cloud Run and serverless architectures.
• Develop and optimize APIs using Google Cloud API Gateway while following security and performance best practices.
• Build and maintain AI/ML data pipelines using Databricks.
• Develop and maintain CI/CD pipelines using GitOps methodologies.
• Manage build artifacts and repositories using JFrog Artifactory and Azure DevOps.
• Work with GCP data services including BigQuery, AlloyDB, Cloud Storage, and Spanner.
• Develop event-driven integrations using Pub/Sub and Kafka.
• Implement Infrastructure as Code using Terraform.
• Collaborate with Product, Data Engineering, and Infrastructure teams to deliver scalable AI solutions.
• Follow GCP security, IAM, encryption, and cloud best practices throughout the development lifecycle.

Benefits

• medical, dental, and vision insurance with an employer contribution
• flexible spending or health savings account
• life and AD&D insurance
• short and long term disability coverage
• paid time off
• employee assistance
• participation in a 401k program with company match
• additional voluntary or legally-required benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior