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# DevOps & Data Engineer - GCP (Google Cloud...

- **Company:** NTT America, Inc.
- **Location:** Alpharetta, GA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $106,840.0 - $160,260.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, BigQuery, Cloud Computing Security, Cloud Engineering, Cloud Storage, Continuous Integration, Information Engineering, DevOps, Identity and Access Management, Python (Programming Language), Machine Learning, Data Processing, Google Cloud, Spring Cloud, Software Application Programming, Backend, Git Flow, Information Technology, Apache Kafka, Cloud Optimization, Api Gateway, Restful APIs, Terraform, Data Pipelines, Serverless Computing, Databricks, Artifactory
- **Published:** August 7, 2026
- **Apply:** https://www.juju.com/job/00000000glx6p6

## About the Role

+ 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.

Preferred Qualifications.

 + Strong analytical, troubleshooting, and problem-solving skills.

 + Good communication and collaboration skills.

Education

 + Bachelor's degree in Computer Science, Engineering, or a related field.

## Description

+ 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. **Required Qualifications**


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