ZipRecruiter

Log In

1

Google Cloud Storage Jobs (NOW HIRING)

Dark Wolf Solutions

Google Cloud Engineer

Herndon, VA · On-site

$57.25 - $76.50/hr

Configuring and managing GCP services such as Compute Engine, App Engine, Google Kubernetes Engine, Cloud Storage, and Cloud SQL. * Architecting and implementing security best practices for GCP ...

Dark Wolf Solutions

Google Cloud Engineer

Tampa, FL · Remote

$52.75 - $70.50/hr

Configuring and managing GCP services such as Compute Engine, App Engine, Google Kubernetes Engine, Cloud Storage, and Cloud SQL. * Architecting and implementing security best practices for GCP ...

MSR Cosmos

Google Cloud ML Engineer

Dallas, TX · On-site

$55.25 - $73.75/hr

Google Cloud ML Engineer- Vertex AI & CCAI Chat Virtual Agent Expert Location: Dallas, TX (Day1 ... Run, Cloud Storage, and BigQuery for real-time data processing, analytics, and reporting.

previous page

Showing results 41-60

All JobsTechnology JobsGoogle Cloud Storage Jobs

Google Cloud Storage information

See salary details

$23K

$131.9K

$237.5K

How much do google cloud storage jobs pay per year?

As of Aug 20, 2026, the average yearly pay for google cloud storage in the United States is $131,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $164,500.00 per year, depending on experience, location, and employer.

What is Google Cloud Storage?

Google Cloud Storage is a scalable, fully managed, and secure object storage service offered by Google Cloud. It allows individuals and organizations to store and retrieve any amount of data at any time, making it ideal for backup, archival, and serving large amounts of unstructured data such as images, videos, and documents. Google Cloud Storage is designed for high durability, availability, and performance, and integrates seamlessly with other Google Cloud services for data analytics, machine learning, and more.

What are the key skills and qualifications needed to thrive as a Google Cloud Storage engineer?

To thrive as a Google Cloud Storage Engineer, you need a solid understanding of cloud storage concepts, networking, security, and experience with Google Cloud Platform (GCP) services, typically backed by a relevant degree or certifications like Google Cloud Professional Cloud Architect. Familiarity with tools such as Google Cloud Console, gsutil, and infrastructure-as-code systems like Terraform is important. Strong problem-solving abilities, attention to detail, and effective communication skills set top performers apart in this role. These skills are crucial for designing, implementing, and managing secure and efficient cloud storage solutions that meet organizational needs.

What are some common challenges faced by professionals working with Google Cloud Storage and how can they be addressed?

Professionals managing Google Cloud Storage often encounter challenges such as optimizing storage costs, ensuring data security, and managing access controls across diverse teams. To address these, it's important to regularly audit storage buckets for unused data, implement lifecycle management policies, and use Identity and Access Management (IAM) roles for granular permission control. Collaborating closely with security and DevOps teams also helps in maintaining compliance and streamlining data workflows, making the environment more efficient and secure.

What is the difference between Google Cloud Storage vs Cloud Data Engineer?

AspectGoogle Cloud StorageCloud Data Engineer
Primary RoleCloud storage service for data storage and retrievalDesigning, building, and managing data pipelines and infrastructure
Required SkillsCloud platform knowledge, data management, basic scriptingData architecture, ETL processes, programming, cloud services
Work EnvironmentCloud environment, storage managementData platforms, cloud environments, cross-functional teams
CertificationsGoogle Cloud Storage-specific certifications, Cloud Engineer certificationsGoogle Cloud Professional Data Engineer, related cloud certifications

Google Cloud Storage is a cloud-based storage service used to store and access data efficiently. In contrast, a Cloud Data Engineer designs and manages data pipelines and infrastructure, often utilizing storage services like Google Cloud Storage. While both roles require cloud platform knowledge and certifications, Cloud Data Engineers focus on data processing and architecture, whereas Google Cloud Storage specialists focus on data storage solutions.

How to get a job at Google Cloud Storage?

To get a job related to Google Cloud Storage, candidates should have experience with cloud computing, storage solutions, and relevant tools like Google Cloud Platform. Building skills in areas such as data management, networking, and obtaining certifications like the Google Cloud Professional Cloud Storage Engineer can improve chances. Applying through Google's careers website and demonstrating technical expertise are key steps.
More about Google Cloud Storage jobs

What cities are hiring for Google Cloud Storage jobs?

Cities with the most Google Cloud Storage job openings:

What job categories do people searching Google Cloud Storage jobs look for?

The top searched job categories for Google Cloud Storage jobs are:

Google Cloud Storage jobs near you
Infographic showing various Google Cloud Storage job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, 2% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $131,885 per year, or $63.4 per hour.

Senior Data Engineer - Google Cloud Platform

Euclid Innovations

Charlotte, NC • On-site

$103K - $140K/yr

Other

Re-posted 13 days ago

Job description

Job Description:

We are looking for a Senior Data Engineer with strong experience in Google Cloud Platform, Spark, and Python to support enterprise data engineering and cloud migration initiatives.

Required Skills:

  • 12+ years of IT experience
  • Strong hands-on experience with Spark and Python (Mandatory)
  • Experience migrating data from on-premises to Google Cloud Platform
  • Strong experience building batch and streaming data pipelines
  • Hands-on experience with BigQuery, Cloud Storage, Dataplex, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and Vertex AI
  • Experience with HDFS, NFS, SQL Server, and object storage
  • Strong understanding of data quality, metadata, schema management, and data lineage
  • Experience supporting ML training and inference workloads, feature engineering, and feature stores
  • Excellent communication and problem-solving skills

Apply