- Data Engineer PH

Position: Data Engineer

Salary Range: 2.000 USD 3.000 USD (Monthly)

Type of contract: Independent contractor

About the Company

We bring deep knowledge of the clinical trial landscape together with cuttingedge AI offering unprecedented agility to research.

Scope of the Role

As a Data Engineer you will be responsible for designing developing and maintaining robust data ingestion pipelines to support our AIdriven clinical trial solutions. You will work with modern data engineering tools such as dbt Apache Airflow Docker and Kubernetes ensuring scalable and reliable data workflows. Additionally you will collaborate with crossfunctional teams and integrate data engineering solutions with machine learning models contributing to the enhancement of patient recruiting efficiency and precision.

Duties and Responsibilities:

• 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 InfrastructureasCode (IaC) tools to manage and provision infrastructure.
• Collaborate with crossfunctional teams including data scientists software engineers and clinical experts.
• Integrate data engineering solutions with machine learning models LLMs and NLP frameworks.
• Stay updated with the latest trends and best practices in data engineering.
• Propose and implement improvements to existing data pipelines and infrastructure.

Requirements:

• 35 years of production experience in data engineering roles (open to senior and junior candidates for the right talent).

• Proficiency with Python Data Engineering stack.
• Handson experience with dbt for data transformation.
• Experience with Apache Airflow or Cloud Composer for workflow orchestration.
• Proficiency with Docker for containerization and Kubernetes for orchestration.
• Experience utilizing CI/CD and InfrastructureasCode (IaC) tools in a production environment.

• Interest or experience in machine learning LLMs and Natural Language Processing (NLP) is highly desirable.
• Strong understanding of data architecture and data modeling principles.
• Familiarity with GitHub for version control and GCP for cloud deployments.