Engineering Manager, Data Platform
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.
Qventus provides 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 and solutions that help nurses, doctors, and hospital staff anticipate issues and make operational decisions proactively. We work with leading public, academic and community hospitals across the United States.
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.
Qventus is looking for an Engineering Manager for our Data Platform team to help build the next generation of our data infrastructure and pipelines. The Data Platform team acts as stewards for Qventus’ data. We stream hospital EMR data to our core warehouses in real time, build out curated data layers to power our Healthcare AI, design and implement patterns to ensure the security of patient (HIPAA) data, and overall ensure Qventus data users have the tools they need to explore and power the Qventus product at scale and cost to improve the lives of patients and doctors across the country.
As an Engineering Manager, you will leverage your existing experience, intuition, and empathy for data users to lead our Data Platform team. You will motivate and foster team development. You will have the ability to make a direct impact on the company by improving the quality of healthcare operations. You will be comfortable designing, supporting, and managing cross-functional initiatives with technical and non-technical stakeholders as well as taking on day to day business impacting workloads when needed. This role will require someone with a keen eye for breaking down the tradeoffs between stability and pragmatic needs, and who can translate this internally and externally to the Engineering org and beyond.
- Lead and champion key initiatives from ideation, through design, to implementation to improve the end-to-end workflow of data users at Qventus, ensuring a high performing, scalable data infrastructure
- Collaborate with non-technical partners to distill requirements, challenges, and outcomes into technical, well defined, and communicated initiatives for the team.
- Hands on support in day to day development needs (expect at least 30-50% IC workload).
- Work within the team and the broader R&D organization to curate, distill, and drive economies of scale that can drive the team forwards efficiently and raise engineering standards.
- Mentor and coach team members to motivate high performance, growth, and long lasting Qventus careers.
- Master’s degree in Computer Science, Engineering, or related field, or equivalent training / experience.
- 2+ years managing and growing data focused engineering teams in fast-paced start up environments.
- Strong business acumen with practical experience working closely with data science and analytics partners.
- Experienced hands-on developer skills, can dive into the weeds to support the team where needed for complex system design or routine implementations; SQL required, Python preferred.
- Demonstrated ability to lead architectural discussion and break down complex technical components for technical and non-technical partners alike.
- Defined philosophy on software development and operational excellence - clean code, release management / CICD.
- Dedication to mentoring and coaching to help mature our technical team and proven ability to drive high quality engineering discourse and development.
Nice to have's:
- Functional practice with scrum team management and Jira or similar work tracking system.
- Design experience in data modeling and transformation pipeline design using modern data technologies: DBT, Snowflake, Airflow, Spark.
- Experience building and maintaining robust and efficient backend data systems with functional proficiency with AWS cloud services and infrastructure as code technologies (Terraform).
- Practical hands on experience with building large-scale, high complexity metrics and monitoring (ELK. Kibana, Datadog).
- Practical hands on experience with data visualization tools (Tableau, Looker preferred).
- Practical hands on experience with data science and machine learning pipelines (Sagemaker, NLP, Tensorflow).
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: https://qventus.com/ccpa-privacy-notice/
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:
Using AI/ML- We use predictive analysis to help doctors and nurses make proactive operational decisions so they can focus on patient care
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.