VI is the market leading Enterprise-AI platform for health, serving the world’s largest health organizations — from Fortune 500 health providers to pharma and consumer brands — helping them maximize acquisition, enrollment, engagement, retention, and health outcomes. Vi offers 3 main product lines: Acquire, Engage and Transform.

Backed by $60M+ in R&D, our powerful platform serves over 100 million members daily — and growing. We are based in New York, Austin, Nashville & Tel Aviv.

We are looking for a talented DATA ENGINEER to join our growing Engineering group.

As a Data Engineer at Vi you will work closely with all R&D teams and business stakeholders to own the entire data process and shape our data strategy.

This is a great opportunity for someone who is passionate about cloud data infrastructure / technologies and wants to make a significant impact in a fast-paced startup environment.

Responsibilities

• Design, develop and implement robust data pipelines using ETL/ELT to move data from various sources into our lakehouse while ensuring scalability, security, and performance
• Ensure quality and integrity of data by implementing validations, testing and monitoring
• End-to-end feature development and ownership, from design to production
• Work directly with stakeholders to develop a solid understanding of the business application and requirements for which the application is being designed

Qualifications

• BSC in a related technical field or equivalent practical experience
• Over 3 years of experience in a Data Engineering role
• Coding experience with Python
• Experience with SQL and NoSQL databases
• Experience with data modeling, and building ELT/ETL pipelines
• Experience with common data warehouse and lakehouse technologies
• Experience with AWS platform
• Experience working with Git, CI-CD flows and Docker
• Experience building data pipelines with big data frameworks such as Spark
• Technologically diverse background and ability/willingness to learn new things quickly

Advantages

• Experience working closely with data scientists/data science projects (MLOps)
• Experience with big data architectures and infrastructures
• Experience with BI tools (Tableau, Looker, Power BI etc.)
• Experience with IaC technologies like CDK & CloudFormation