Data Scientist Engineer

Compunnel, Inc.; Town of Florida (NY); On-site; USD 100,000 - 130,000; Full time

Job summary

A technology company is seeking an experienced Data Science Engineer to develop production-level data pipelines and enable scalable machine learning workflows. Candidates should have strong expertise in Python, GCP, and CI/CD, and will work closely with Data Scientists and ML Engineers in a dynamic environment.

Qualifications

• Minimum 5 years of experience in Data Engineering or a related field.
• Strong programming skills in Python, with experience in relevant libraries and frameworks.
• Hands-on experience with CI/CD pipelines and automation tools.
• Proficiency in containerization using Docker and Kubernetes.
• Solid understanding of GCP (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 for cross-functional teamwork.

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 cloud solutions using GCP or AWS, ensuring scalability, security, 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 software development best practices.

Skills

Python

GCP

CI/CD

Docker

Kubernetes

Vertex AI

Job description

We are seeking a Data Science Engineer to join a specialized project team focused on building production-level data pipelines and enabling scalable machine learning workflows.

The ideal candidate will have strong expertise in Python, GCP, CI/CD, Docker/Kubernetes, and Vertex AI, and will collaborate closely with Data Scientists and ML Engineers in a fast-paced environment.

Key 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 cloud solutions using GCP or AWS, ensuring scalability, security, 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 software development best practices.

Required Qualifications

• Minimum 5 years of experience in Data Engineering or a related field.
• Strong programming skills in Python, with experience in relevant libraries and frameworks.
• Hands-on experience with CI/CD pipelines and automation tools.
• Proficiency in containerization using Docker and Kubernetes.
• Solid understanding of GCP (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 for cross-functional teamwork.

Preferred Qualifications

• Experience with Q Flow and advanced ML workflow orchestration.
• Exposure to LLM-based solutions and production-level AI systems.