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# Associate Data Engineer - GCP

- **Company:** Capgemini
- **Location:** Atlanta, GA, United States
- **Salary:** $71,973.0 - $96,800.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Google App Engines, BigQuery, Cloud Computing, Cloud Computing Security, Cloud Engineering, Cloud Storage, Computer Programming, Databases, Continuous Integration, Data Flow Control, Python (Programming Language), Machine Learning, NoSQL, Tensorflow, SQL Databases, Data Processing, Google Cloud, Large Language Models, Git, Scikit Learn, Kubernetes, Restful APIs, Data Pipelines, Docker, Microservices
- **Published:** July 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=8432eda41e25a208

## About the Role

We are looking for a motivated AI & Google Cloud Engineer with hands-on experience in building scalable applications using GCP services and basic AI/ML concepts. The candidate should have strong programming skills and a good understanding of cloud-based solutions., * Strong programming skills in Java / Python.

 * Hands-on experience with:
 + Google Cloud services (Compute Engine, Cloud Functions, App Engine)
 + Git, CI/CD tools
 * Basic understanding of:
 + Machine Learning concepts
 + APIs and microservices
 * Familiarity with databases:
 + SQL, BigQuery, NoSQL
 * Experience with Docker / Kubernetes (GKE)
 * Knowledge of data processing tools like Dataflow
 * Exposure to GenAI or LLM APIs
 * GCP Associate Cloud Engineer certification

## Description

* Develop, test, and deploy applications using **Google Cloud Platform (GCP)** services
 * Build and integrate **basic AI/ML models** using tools like:
 + Vertex AI
 + AutoML
 + TensorFlow / Scikit-learn
 * Work with REST APIs and microservices architecture
 * Implement data pipelines using BigQuery, Cloud Storage, Pub/Sub
 * Collaborate with cross-functional teams to understand requirements
 * Troubleshoot and optimize cloud-based solutions Follow best practices for cloud security, scalability, and cost optimization
*


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