About the opportunity
The company is looking for a Data Engineer II to help build the next generation of their data ecosystem as part of their Data Platform team. The Data Platform team acts as stewards for Qventus’ data. They 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. Their services support both internal & external decision making from product development and client insights to ultimately supporting the development and operationalization of their Healthcare AI to improve the lives of patients and doctors across the country.
As a Data Engineer II, you will build and maintain significant components of the Qventus data architecture for their 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.
✓ 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.
Demonstrated experience in leading data modeling & transformation pipeline design for production services and data science / analytics partner needs (strong SQL & DBT experience preferred).
Required Technologies and Skills -
Nice to have (Big plus)
Benefits and terms