Overview
Hybrid
$65 - $70
Accepts corp to corp applications
Contract - Independent
Contract - W2
Skills
Amazon Web Services
Apache Beam
Cloud Computing
Cloud Storage
Collaboration
Continuous Delivery
Continuous Integration
Data Flow
Data Modeling
Data Processing
Data Quality
Data Warehouse
DevOps
Docker
ELT
Extract
Transform
Load
Git
Good Clinical Practice
Google Cloud
Google Cloud Platform
Kubernetes
Machine Learning (ML)
Microsoft Azure
Optimization
Orchestration
Python
Real-time
Regulatory Compliance
SQL
Scalability
Streaming
Terraform
Unstructured Data
Warehouse
Workflow
Job Details
Job Title: Google Cloud Platform Data Engineer
Location: hybrid
Job Summary:
We are seeking an experienced Google Cloud Platform (Google Cloud Platform) Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate will have strong expertise in Google Cloud Platform data services, ETL/ELT processes, and data modeling, ensuring efficient and secure data flow across the organization.
Key Responsibilities:
Design, develop, and deploy data pipelines using Google Cloud Platform services such as Dataflow, Dataproc, BigQuery, Pub/Sub, and Cloud Composer (Airflow).
Implement ETL/ELT workflows for structured and unstructured data sources.
Build and maintain data warehouses and data lakes using BigQuery, Cloud Storage, and related tools.
Collaborate with data analysts, data scientists, and application teams to deliver reliable, high-quality datasets.
Optimize data performance, scalability, and cost within the Google Cloud Platform ecosystem.
Ensure data quality, governance, and security best practices.
Use Terraform or Deployment Manager for infrastructure automation.
Monitor, troubleshoot, and improve existing data workflows and pipelines.
Required Skills and Qualifications:
Bachelor s degree in Computer Science, Information Technology, or related field.
Proven experience working with Google Cloud Platform (Google Cloud Platform).
Strong proficiency in SQL and Python for data processing.
Hands-on experience with BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Cloud Composer.
Knowledge of data modeling, schema design, and warehouse optimization.
Experience with CI/CD pipelines, Git, and DevOps practices.
Familiarity with Apache Beam, Airflow, or other orchestration tools.
Understanding of security and compliance in cloud data environments.
Preferred Qualifications:
Google Cloud Platform Professional Data Engineer Certification.
Experience with machine learning pipelines or real-time data streaming.
Exposure to Docker, Kubernetes, or DataOps frameworks.
Experience in multi-cloud or hybrid environments (AWS, Azure)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.