Have you ever found yourself or a loved one waiting hours and hours in a hospital Emergency Room to get care? Or have you ever had a surgery scheduled for months in the future that needed to happen sooner? Unfortunately, our healthcare system is full of these types of operational problems. Our work saves lives and helps hospitals cut tens of millions of dollars in operational costs, while improving the quality of care they’re able to deliver.
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 Engineer to help build the next generation of our data ecosystem as part of our Data Platform team. The Data Platform team acts as stewards for Qventus’ data. We manage the data ecosystem from technical infrastructure to data architecture and tactical data transformations to unlock data as strategic asset in powering high quality decision making at scale. Our services support both internal & external decision making from product development and client insights to ultimately supporting the development and operationalization of our Healthcare AI to improve the lives of patients and doctors across the country.
As a Data Engineer, you will build and maintain significant components of the Qventus data architecture for our Periop solution. You will be comfortable working closely with both core data users on analytics and data science and backend partners to design, build, and deploy comprehensive data pipelines in support of internal and external data solutions - from data requirement & quality definitions, to pipeline design, to feature engineering within the healthcare space (and HIPAA restrictions). 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.
Key Responsibilities
- Build, tune, and improve the end-to-end workflow of data users at Qventus to data driven decisions & product features (incl. designing data structures, building and scheduling data transformation pipelines, improving access to critical data assets etc.).
- Improve the overall definition and quality of our data assets incl. the automation and management of schema lifecycles, improved tooling for data flow visibility, and data quality tooling/monitoring
- Support the optimization and scale of existing pipelines, dashboards, and data science feature engineering to support Qventus scale
- Collaborate with data infrastructure and engineering teams to build, extend, and envision cross-platform ETL and reports generation frameworks to raise engineering standards.
Key Qualifications
- Demonstrated experience in data modeling and transformation pipeline design and experience building for data science and analytics partner needs (strong SQL)
- Working, hands on, knowledge of modern Data Pipeline tools (DBT, Snowflake, Airflow) and Data visualization tools (Looker)
- Experience working and building in a fast paced dynamic environment across multiple technologies
- 3-5+ years of professional experience working with modern programming languages such as Python (preferred), Java, Go, C++ and a dedication to high code quality.
Nice to Have
- Strong cross-functional communication - ability to break down complex technical components for technical and non-technical partners alike.
- Practical hands on experience with data lake / schema discovery systems and relevant technologies (Confluent/Kafka, Spark, Athena/Glue, DynamoDB etc.)
- Familiarity with the AWS ecosystem (Lambda, RDS, Redshift etc.)
- Experience handling unstructured data, especially working with NLP tooling to extract information from text
- Bachelor’s degree in Computer Science, Engineering, Analytics, or related field, or equivalent training / experience
