Data Engineer

Gruve • California, PA

5d

About The Position

We are seeking a skilled Data Engineer to design, build, and maintain end-to-end data pipelines and scalable infrastructure that supports machine learning models for the Data Science team and other business units. This role involves close collaboration with data scientists, researchers, and cross-functional technology teams to understand data processing and analytics requirements and translate them into effective technical solutions. You will also troubleshoot infrastructure issues, analyze data flows across company applications, and ensure reliable, secure, and compliant system operations in both production and non-production environments.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent work experience.
• 3+ years of experience building data infrastructure for analytics teams.
• Strong coding skills in SQL, Python, or R for processing large datasets in distributed cloud environments.
• Experience with cloud deployment strategies and CI/CD pipelines.
• Experience with SaaS-based data infrastructure.
• Knowledge of multiple programming languages with willingness to learn new languages as needed.
• Familiarity with resource management and workflow automation tools.
• Collaborative mindset and ability to work closely with data science teams.

Nice To Haves

• Hands-on experience with machine learning model deployment and monitoring.
• Experience with healthcare data or regulated industries.
• Knowledge of modern workflow orchestration tools (e.g., Airflow, Prefect).
• Strong understanding of data security, compliance, and governance best practices.
• Experience in optimizing data pipelines for performance and cost-efficiency.

Responsibilities

• Design, develop, and maintain data pipelines and infrastructure to support machine learning solutions.
• Collaborate with data scientists and technology teams to understand analytics requirements and implement technical designs.
• Support development, validation, and deployment of machine learning models on healthcare and other business data.
• Analyze data flows across company applications to guide technology and platform decisions.
• Troubleshoot infrastructure issues across production and non-production environments.
• Partner with Technology and Digital Solutions teams to ensure secure, reliable, and compliant system operations.
• Participate in iterative design and continuous improvement of data infrastructure.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level