Senior Data Engineer

present of AI; United States; A distancia; USD 140.000 - 190.000; Jornada completa

Descripción de la vacante

Qventus is seeking a senior data engineer to design, build and maintain data pipelines and models for AI-driven hospital scheduling and discharge planning. You will own data quality and scale across teams, shaping data models and ensuring reliable data for analytics and products.

The role emphasizes working with SQL, a modern programming language, and orchestration tools, with hands-on exposure to data validation, monitoring and model feeding in real-world healthcare datasets.

Formación

• Design, build and maintain reliable data pipelines and models.
• Own data quality and scale across teams.
• Experience with SQL, a modern programming language and orchestration tools.

Responsabilidades

• Design, build and maintain data pipelines supporting AI-driven hospital scheduling and discharge planning.
• Ensure data quality, timeliness and reliability for analytics and product teams.
• Collaborate with data scientists and engineers to shape data models for analytics.

Conocimientos

SQL

Modeling

Orchestration tools

Descripción del empleo

A senior data engineer is typically expected to design, build and maintain reliable data pipelines and models that others depend on, and to take ownership of data quality and scale. A strong candidate brings solid experience with SQL, a modern programming language and orchestration tools, plus the judgment to shape data models for analytics and products. At a company building AI operational assistants for hospital scheduling and discharge planning, that means pipelines that keep operational data accurate and timely for the teams relying on them.

How it fits the AI era

AI tools speed up parts of pipeline code, testing and documentation, so the role shifts toward design choices, data contracts and judgment about what data is trustworthy. The human core stays in understanding messy healthcare data, setting quality standards and deciding how systems should behave when data is late or wrong. Reliable data plumbing is what makes AI assistants useful rather than misleading.

How it builds AI experience

Working here offers hands on exposure to data that feeds AI operational assistants, including the quality and freshness demands that come with them. Experience with data validation, pipeline monitoring and feeding models or analytics products is worth building. Practicing on realistic operational datasets and learning how model inputs are prepared would strengthen a candidacy.

Worth showing

• SQL and modeling
• Orchestration tools

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Qventus

AI operational assistants that handle the scheduling, discharge planning and case-selection busywork behind hospital operations.