Senior Data Engineer

Vivian Health empowers every healthcare professional to find their perfect job faster and easier than ever before. As the largest healthcare jobs marketplace, we support over 2 million clinicians in finding their next career opportunities. Our AI-driven platform also enhances process efficiencies for staffing agencies and healthcare employers, significantly reducing time to hire.

Vivian Health is backed by world-class investors, including Thoma Bravo and IAC, with over $75 million in capital raised. Our accolades include BuiltIn's awards for "Fully Remote Best Startup," "Fully Remote Best Places to Work," and "U.S. Best Startups to Work For" in 2024.

About the team

Vivian Health is a remote-first company at the forefront of transforming the healthcare staffing landscape. The Data Team plays a critical role in providing insights that drive business strategy and empower data-driven decision making across the organization. Our team is a centralized group of talented data professionals, with experience across BI and analytics, engineering, data science, and machine learning. We are looking for an experienced data engineer to help shape the future of our data platform.

What you'll do

As a Senior Data Engineer, you will design, build, and maintain the core data infrastructure that powers Vivian Health. You'll take ownership of complex technical projects, drive architectural decisions, and serve as a technical mentor to other engineers on the team. A key focus will be building and maintaining feature stores and ML infrastructure to power our machine learning models, enabling personalized experiences for millions of healthcare professionals.

What we're looking for

We're looking for an experienced engineer who combines deep data engineering expertise with strong problem-solving skills and a collaborative mindset. Ideally, you bring:

• 5+ years of professional experience in data engineering or software engineering
• Proven experience designing and building data pipelines and platforms at scale
• Strong proficiency in Python and SQL
• Deep expertise with cloud data warehouses like Snowflake, BigQuery, or Redshift
• Experience building and maintaining feature stores and ML infrastructure
• Knowledge of AWS technologies like DynamoDB, Lambda, SageMaker, and Kinesis
• Experience with Infrastructure-as-Code tools like CloudFormation or Terraform
• Experience with Airflow, DBT, and data orchestration best practices
• Hands-on experience with streaming data pipelines (Kafka, Kinesis, or similar)
• Ability to mentor junior engineers and contribute to technical standards
• Strong communication skills with the ability to collaborate across technical and non-technical teams