Qventus is a real-time decision-making platform for hospital operations. Our mission is to simplify how healthcare operates, so that hospitals and caregivers can focus on delivering the best possible care to patients.
We combine machine learning, generative AI, and behavioral science to create products that help nurses, doctors, and hospital staff anticipate issues and make operational decisions proactively.
At Qventus, you will have the opportunity to work with an exceptional, mission-driven team across the globe, and the ability to directly impact the lives of patients. We’re inspired to work with healthcare leaders on our founding vision and unlock world-class medicine through world-class operations.
We’re looking for a Senior Data Engineer who can bring strong data modeling and pipeline development experience, paired with curiosity and initiative to solve real-world problems to help shape and scale the data that powers our Inpatient solution. The Inpatient Data Engineering team serves as the stewards and activators for Qventus data - ensuring it is accessible, reliable, and actionable to power core product experiences and healthcare outcomes. Our pipelines and systems transform complex, messy EHR data into curated models, ensure synchronicity between internal applications and EHR applications, and ultimately provide near real time insights and actions that drive interventions to reduce length of stay, unblock discharges, and improve patient flow across the hospital allowing care teams to provide a higher level of care.
As a Senior Engineer, you’ll lead the design, implementation, and improvement of scalable, efficient pipelines to support our data intensive products - from integrating new data to enhancing the foundation of our unified data model to partnering with Data Scientists or Decision experts to operationalize feature pipelines. You should be curious, proactive, and a strong self-starter - excited to dive into ambiguous problems and take initiative without waiting for direction. You thrive in fast-moving environments and enjoy collaborating with or leading teammates to build solutions, not just deliver tasks.
You will be adept in partnering with cross-functional partners, product, and data users to translate needs into technical solutions and data definitions. You’re motivated by understanding how data connects to real-world impact, and bring strong data intuition, business logic, and a desire to understand the underlying systems, relationships, and causal patterns behind the data. You’ll be excited to join an amazing mission driven team and take on new challenges quarter over quarter - growing yourself and our healthcare solutions!
Develop and maintain reliable daily and near real-time pipelines that ingest and process healthcare data from hospital EHR, enabling timely, high-quality data delivery for Inpatient product use cases.
Drive evolution toward a medallion architecture, contributing to the design, implementation, and migration for the Qventus foundational data model in the Inpatient Hospital domain
Partner with Product and cross-functional teams to deeply understand end-user and clinical needs, translating them into robust, scalable data models and transformation pipelines.
Maintain and improve our event-based architecture solutions
Support execution against key client implementations and team deliverables - jumping in wherever is needed to hit core team objectives (analytics engineering, decision engine support logic etc.)
Proficiency developing SQL and Python (for data processing, pandas etc.) in production engineering environments (git, github actions, release automations etc.); Experience with dbt (data build tool)
3+ years professional experience using modern Data Warehousing platforms - AWS, Snowflake, and/or Databricks preferred, with demonstrated experience in quality data pipeline design, development, and optimization and basic understanding of medallion architectures
Effective cross-functional communicator, capable of translating technical concepts into clear narratives for product, clinical, and engineering stakeholders; adept at surfacing trade-offs, aligning priorities, and building shared understanding.
Innate aptitude for interpreting complex datasets with demonstrated ability to discern underlying patterns, identify anomalies, and extract meaningful insights, demonstrating advanced data intuition and analytical skills.
Proven ability to navigate ambiguity and solve open-ended problems by understanding real-world needs, identifying cross-data relationships, and collaborating with cross-functional teams to design practical, context-aware data solutions that shape product development.
Experience leveraging GLUE of AWS cloud services for production systems
Experience supporting event driven systems & streaming data pipelines - experience with Kafka a plus!
Experience building / supporting modern BI tools (Sigma preferred) and supporting analytics engineering development (metrics, semantic layer etc.)
Degree in Computer Science, Engineering, or related field
Experience working with healthcare data and HIPAA data protection
Originally posted on Himalayas
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