Data Platform Architect at Qventus (W15)
$170K - $200K  •  
We automate operations for hospitals and health systems
Mountain View or Remote / Remote (US)
6+ years
About Qventus

We are a team of technologists, software engineers, doctors, nurses, and lean healthcare experts with on-the-ground experience solving operational challenges in clinical environments. Qventus helps hospitals like Stanford/Mayo Clinic/Emory/New York Presbyterian reduce wait time for patients, prevent patient falls, and generally helps hospitals deliver a better and safer experience for patients, resulting in reduced injuries, loss of life, and financial waste.

We're making a big difference. Qventus has meaningfully affected patient experiences and outcomes for almost 4 million patients across the united states. Our platform works with hospital data to predict negative outcomes for patients and associated potentially disastrous situations that are likely to occur, then applies our system of action to reach the right doctors and nurses, at the right time, telling them where to go to stop these events before they happen. Think Minority Report applied to hospitals.

Our founding team has done this before. Two of our three founders worked in consulting for over a decade solving efficiency problems in hospitals. They know hospitals, where they've been, where they want to go, and how to work within them to drive the necessary mind shift and change management we need to drive this new wave of technology.

Our team is top notch! We have the fortune of having amazing engineerings and data scientists from top schools (Stanford, MIT, Cal, etc.) applying the latest in artificial intelligence and machine learning to create products that help healthcare organizations around the world and their people adapt in the moment and make the right decisions from the most complex data. Furthermore, we employ several practicing clinicians (practicing surgeons, doctors, nurses) in the company to help us understand the hospital environment. We take what we do very seriously.

About the role
Skills: TensorFlow, Data Modeling, Data Analytics

The Company

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 use artificial intelligence and machine learning to create products that help nurses, doctors, and hospital staff anticipate issues and make operational decisions proactively.

Qventus works with leading public, academic and community hospitals across the United States. The company was recognized by the 2019 Black Book Awards in healthcare for patient flow and by CB Insights as a 2019 top 100 Most Promising Company in Artificial Intelligence. Recently, Qventus won the Robert Wood Johnson Foundation Emergency Response for the Healthcare System Innovation Challenge through its work helping health systems across the country plan for and operate in the COVID pandemic.

The Role

Qventus is looking for a Data Platform Architect to lead the next generation of our data platform. Our Data team ensures that Qventus data users have the tools and data they need to explore and power the Qventus product at scale and cost. This includes bidirectional integration with hospital EMR sources via multiple channels (FHIR), complex highly secure (HIPAA) transformations capable of normalizing information across various workflows and client nuances, integration with multiple third party datasets from customer data to big-data claims, and more. Our products span the machine learning based orchestrations, real time hospital reporting, analytical insights, and interactive applications needed to improve the lives of patients and doctors across the country.

As a Data Platform Architect, you will oversee and lead the design, development, and management of our data platform infrastructure to ensure our data platform remains scalable, reliable, and efficient in light of evolving data requirements of our products and services. You will be comfortable identifying, designing and leading cross-functional initiatives to improve the data ecosystem with a strong understanding of organizational impact, risks, and trade-offs. You will be motivated and excited to have an impact on the team and in the company and to improve the quality of healthcare operations.

Core Responsibilities

  • Lead identification, design, and execution of critical improvements to our platform to maintain overall system health and functionality in support of evolving platform requirements and data user needs (incl. significant technology migrations)

  • Work with senior engineering leaders and data users across the organization to define & communicate the technical vision and strategy for the data platform

  • Establish & enforce processes, tooling, and best practices for effective data observability (quality metrics/monitoring, metadata, lineage etc.) and infrastructure management (cost, performance, reliability etc.)

  • Provide expertise on the overall data engineering best practices, standards, architectural approaches and complex technical resolutions

  • Tactically support development against company deliverables (expect at least 50% IC workload incl. POC development and production code)

  • Facilitate the growth and development of senior team members by actively providing hands-on technical guidance and fostering a collaborative work environment.

Key Requirements

  • Strong cross-functional communication - ability to break down complex technical components for technical and non-technical partners alike

  • Expertise building, designing, and developing on a diverse set of modern data architecture designs and their relative capabilities and use cases (ex. Data Lake, Lakehouse, Lambda)

  • Mastery of quality data pipeline design, development, and optimization to create reliable, modular, secure data foundations for the organization's data delivery system

  • 5+ years of experience designing, building, and operating cloud-based, highly available, observable, and scalable data platforms utilizing large, diverse data sets in production to meet ambiguous business needs

  • 2+ years managing and leading technical architecture decisions and design with a strong grasp of architectural design frameworks

  • Interest in mentoring and supporting new developers

Nice to have skills

  • Experience defining data engineering/architecture best practices at a department and organizational level and establishing standards for operational excellence and code and data quality at a multi-project level

  • Relevant industry certifications in a variety of Data Architecture services (SnowPro Advanced Architect, Azure Solutions Architect Expert, AWS Solutions Architect / Database, Databricks Data Engineer / Spark / Platform etc.)

  • Experience designing and supporting multi-cloud architectures (particularly for ML / AI systems)

  • Experience with data visualization tools and analytics technologies (Looker, Tableau, etc.)

  • Experience developing and maintaining Data Science / Machine Learning models or architecture (Sagemaker, Tensorflow, Azure ML); experience with productionalized Generative AI (ChatGPT) desired

  • Degree in Computer Science, Engineering, or related field

  • General experience with broader system design and efficient backend data optimization

  • Experience working with healthcare data and HIPAA data protection

We consider several factors when determining compensation, including location, experience, and other job-related factors.

Salary Range: $170,000 to $200,000 annually + equity + benefits- Qventus expects to hire for this position near the middle of the range. Only in truly rare or exceptional circumstances where a candidate's experience, credentials, or expertise far exceed those required or expected will we consider and offer at the top of the salary range.

Qventus offers a competitive benefits package including medical, dental, vision, paid time off, company holidays, and a stock option plan.

Qventus is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.

Candidate information will be treated in accordance with our candidate privacy notice which can be found here:

This position does not provide visa sponsorship.

Employment is contingent upon the satisfactory completion of our pre-employment background investigation and drug test.



Engineering is comprised of several teams: - Web Apps: Responsible for our web platform and associated services. - Mobile: Responsible for our mobile products (iOS and Android). - Data Platform: Responsible for ETL, data processing and platform, managing data lifecyle from customer ingest to persistence, serving data to data science and web apps groups. - Data Science: Responsible for our ML development. - DevOps: Infrastructure and associated infrastructure services, working with teams to build and maintain CI/CD pipelines. - QA: Responsible for quality definition, automation, QA infrastructure, driving quality process from development through release. Functional QA is largely outsourced, we prefer to have QA team focused more on the engineering required to scale a large QA org.

Some of the challenges we are facing:

  1. Using AI/ML- We use predictive analysis to help doctors and nurses make proactive operational decisions so they can focus on patient care

  2. Data scaling- We are starting to get significantly larger volumes of data, which is also increasingly becoming more and more clinical (lab results, etc) in nature.

3)Data sensitivity- Because this data is more clinical, it is more sensitive and requires a higher bar on how we set up and monitor our systems.

4)Data Ingestion- Getting data out of hospitals is not an easy task. We have to figure out more scalable solutions to help us grow quickly. This is an industry wide problem and we are looking to do it better than just about anyone else.

5)Product growth- Expansion in more areas of the hospital means we have more to learn and an opportunity to expand our product to achieve more outcomes.

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