Overview
0.0
Contract - W2
Skills
Continuous Integration and Development
Scalability
Regulatory Compliance
Testing
Data Integrity
Management
API
Workflow
Software Development
Data Engineering
Python
Continuous Integration
Continuous Delivery
Docker
Kubernetes
Google Cloud Platform
Google Cloud
Amazon Web Services
Microsoft Azure
Vertex
Artificial Intelligence
Machine Learning (ML)
Orchestration
Data Security
Cloud Computing
Communication
Collaboration
Job Details
Role:Data Scientist Engineer
Location:REMOTE
Duration:12 Months
Required Skills :
5+ years of experience in Data Engineering
Strong Python from a programming perspective
Experience with CICD Pipelines
Experience with Containerization using Docker/Kubernetes
Google Cloud Platform cloud experience
Strong communication skills; should be able to collaborate with team members
Additional Skills :
Experience with Vertex AI/Gemini AI
Day-to-Day Responsibilities
Design, develop, and maintain data pipelines for machine learning models using Python and Vertex AI.
Collaborate with Data Scientists and ML Engineers to operationalize propensity models and LLM-based solutions.
Implement Google Cloud Platform/AWS cloud solutions, ensuring security, scalability, and compliance.
Build and manage CI/CD pipelines for automated deployments and testing.
Containerize applications using Docker and orchestrate with Kubernetes.
Monitor data integrity, security, and performance across cloud environments.
Create and manage API endpoints for model integration and data services.
Utilize Q Flow for Vertex AI to streamline ML workflows and pipeline execution.
Ensure production-level code quality and adherence to best practices in software development.
Qualifications
5+ years of experience in Data Engineering or related field.
Strong programming skills in Python, including experience with relevant libraries and frameworks.
Hands-on experience with CI/CD pipelines and automation tools.
Proficiency in containerization using Docker and Kubernetes.
Solid understanding of Google Cloud Platform (preferred) or similar cloud platforms (AWS/Azure).
Familiarity with Vertex AI and ML pipeline orchestration.
Knowledge of data security and monitoring in cloud environments.
Excellent communication and collaboration skills to work closely with cross-functional teams.
Location:REMOTE
Duration:12 Months
Required Skills :
5+ years of experience in Data Engineering
Strong Python from a programming perspective
Experience with CICD Pipelines
Experience with Containerization using Docker/Kubernetes
Google Cloud Platform cloud experience
Strong communication skills; should be able to collaborate with team members
Additional Skills :
Experience with Vertex AI/Gemini AI
Day-to-Day Responsibilities
Design, develop, and maintain data pipelines for machine learning models using Python and Vertex AI.
Collaborate with Data Scientists and ML Engineers to operationalize propensity models and LLM-based solutions.
Implement Google Cloud Platform/AWS cloud solutions, ensuring security, scalability, and compliance.
Build and manage CI/CD pipelines for automated deployments and testing.
Containerize applications using Docker and orchestrate with Kubernetes.
Monitor data integrity, security, and performance across cloud environments.
Create and manage API endpoints for model integration and data services.
Utilize Q Flow for Vertex AI to streamline ML workflows and pipeline execution.
Ensure production-level code quality and adherence to best practices in software development.
Qualifications
5+ years of experience in Data Engineering or related field.
Strong programming skills in Python, including experience with relevant libraries and frameworks.
Hands-on experience with CI/CD pipelines and automation tools.
Proficiency in containerization using Docker and Kubernetes.
Solid understanding of Google Cloud Platform (preferred) or similar cloud platforms (AWS/Azure).
Familiarity with Vertex AI and ML pipeline orchestration.
Knowledge of data security and monitoring in cloud environments.
Excellent communication and collaboration skills to work closely with cross-functional teams.
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.