Data Engineer - Remote

Overview

As a Data Engineer, you will be responsible for designing, developing, and maintaining robust data ingestion pipelines to support our AI-driven clinical trial solutions.

In Short

• Design, develop, and maintain robust data ingestion pipelines.
• Ensure data pipelines are scalable, reliable, and efficient.
• Monitor and optimize the performance of data workflows.
• Work with dbt for data transformation and modeling.
• Use Apache Airflow or Cloud Composer for orchestrating workflows.
• Implement containerization with Docker and orchestration with Kubernetes.
• Manage code via GitHub and deploy solutions on Google Cloud Platform (GCP).
• Implement Continuous Integration/Continuous Deployment (CI/CD) practices.
• Utilize Infrastructure-as-Code (IaC) tools to manage and provision infrastructure.
• Collaborate with cross-functional teams including data scientists, software engineers, and clinical experts.

Requirements

• Experience in data engineering and building data pipelines.
• Proficiency in dbt, Apache Airflow, Docker, and Kubernetes.
• Familiarity with Google Cloud Platform (GCP).
• Knowledge of CI/CD practices.
• Experience with Infrastructure-as-Code tools.
• Ability to collaborate with cross-functional teams.
• Understanding of machine learning models and frameworks.
• Strong problem-solving skills.
• Ability to stay updated with industry trends.
• Excellent communication skills.

Benefits

• Work with cutting-edge AI technology.
• Flexible working hours.
• Opportunity to contribute to clinical trial solutions.
• Collaborative work environment.
• Professional development opportunities.