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Google Cloud Platform Internship Jobs (NOW HIRING)

Machine Intelligence Technologies, LLC

$124 - $207/hr

Google Cloud Platform Cloud Architect/ GKE Tech Lead Location: Bellevue, WA Duration: 24Months+ Extension Hourly Rate: Depending on Experience (DOE) Work Authorization: Role: G Google Cloud Platform ...

Stefanini

Google Cloud Platform Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a Google Cloud Platform Data Engineer, Dearborn, MI For quick apply, please reach out to Lovkesh Bharti at / We are responsible for designing, building, and maintaining data ...

Intraedge

Google Cloud Platform Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Google Cloud Platform Data Engineer (Day 1 onsite - Hybrid 3 days a week in office) Location: Phoenix, AZ Duration: Long Term Contract Expert in SQL and Data warehousing concepts. Hands-on experience ...

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How much do google cloud platform internship jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for google cloud platform internship in the United States is $18.84, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.47 per hour, depending on experience, location, and employer.

What is a Google Cloud Platform internship?

A Google Cloud Platform (GCP) Internship is a temporary position, typically for students or recent graduates, where individuals work at Google or with partner organizations to gain hands-on experience with Google's cloud computing technologies. Interns work on real-world projects involving cloud infrastructure, data analytics, machine learning, and application development using GCP tools. The internship provides mentorship, technical training, and networking opportunities, helping participants build valuable skills for a career in cloud computing and technology.

What do I do during a Google Cloud Platform internship?

As a Google Cloud Platform Intern, you can expect to work on hands-on projects involving cloud infrastructure, application development, and data analytics. Interns often collaborate with teams to design, implement, and test cloud-based solutions that address real business needs. Responsibilities may also include automating processes, optimizing cloud resources, or contributing to open-source projects. You’ll have the opportunity to learn from experienced engineers, participate in team meetings, and gain exposure to Google’s agile development environment.

What skills and qualifications are needed for a Google Cloud Platform internship?

To thrive as a Google Cloud Platform (GCP) Intern, you need a solid understanding of cloud computing concepts, programming skills (such as Python or Java), and enrollment in or completion of a relevant degree program. Familiarity with GCP tools like Compute Engine, BigQuery, and Cloud Storage, as well as foundational certifications such as the Google Associate Cloud Engineer, are highly valued. Strong problem-solving abilities, eagerness to learn, and effective teamwork and communication skills make an intern stand out. These skills are crucial for successfully contributing to cloud-based projects, adapting to dynamic environments, and collaborating with diverse teams.

What is the difference between Google Cloud Platform Internship vs Cloud Engineer Intern?

AspectGoogle Cloud Platform InternshipCloud Engineer Intern
Required CredentialsBasic knowledge of cloud concepts, coursework, or certifications like GCP FundamentalsSimilar; often includes familiarity with cloud platforms and basic programming skills
Work EnvironmentHands-on projects within Google Cloud environment, collaborative teams, learning-focusedPractical cloud infrastructure tasks, support roles, team collaboration
Employer & Industry UsageGoogle, tech industry, cloud servicesVarious tech companies, cloud service providers, startups

The Google Cloud Platform Internship is designed for students or beginners interested in cloud technology, focusing on learning and supporting Google Cloud services. A Cloud Engineer Intern may have similar responsibilities but often involves more technical tasks related to cloud infrastructure. Both roles serve as entry points into cloud careers, with the internship emphasizing learning and exposure.

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Google Cloud Platform Internship jobs near you
Infographic showing various Google Cloud Platform Internship job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, 47% Part Time, and 3% Contract. Highlights an 78% Physical, 2% Hybrid, and 20% Remote job distribution, with an average salary of $39,193 per year, or $18.8 per hour.

Google Cloud Platform Data Engineer

Rivago infotech inc

Manor, TX • On-site

$123K - $148K/yr

Other

Posted 5 days ago

Job description


Role: Senior Google Cloud Platform Data Engineer (ML & Fraud Analytics Data Platform)

Location: Austin TX (100% Onsite)

Duration: Long term Project

Cloud Platform: Google Cloud Platform

Skills Required: Google Cloud Platform, BigQuery, Python, Dataflow, Composer/Airflow, Google Cloud Storage (GCS)

 

Key Responsibilities & Skills

·        Design, develop, and maintain scalable ETL/data pipelines on Google Cloud Platform using Python, Dataflow, BigQuery, Cloud Storage, Composer/Airflow, and Control-M to support fraud analytics, ML, and enterprise data initiatives.

·        Build and optimize ML-ready datasets, feature engineering pipelines, and reusable data assets for model training, validation, and production deployment.

·        Develop high-quality Python solutions following coding standards, security best practices, resiliency, reliability, and performance optimization principles.

·        Strong expertise in SQL, BigQuery/PostgreSQL, data modelling, database concepts, and large-scale data processing.

·        Implement data quality, reconciliation, lineage, metadata management, governance, and monitoring controls to ensure trusted and auditable data pipelines.

·        Design and support CI/CD-enabled data engineering platforms, automated deployments, and integration with enterprise data ecosystems including Dataiku, Neo4j, REST APIs, and cloud-native services.

·        Collaborate with Data Scientists and ML Engineers to support feature availability, data access, pipeline orchestration, integration testing, and ML operationalization.

·        Strong analytical, problem-solving, and troubleshooting skills; exposure to GenAI use cases and MLOps ecosystems is a plus.

 

Preferred Experience

·        Overall 10+ years of experience 

·        5+ years on Google Cloud Platform Data Engineering

·        5+ years with Python/Dataflow-based ETL development

·        3+ years with Composer/Airflow, BigQuery/PostgreSQL, and Google Cloud Storage

·        Experience supporting fraud detection, risk analytics, or ML data platforms preferred.

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