Lead Data Engineer

Vivian Health

8d•$190,000 - $220,000•Remote

About The Position

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 a technical leader to help guide the team and shape the future of our data platform. As Lead Data Engineer you will set the technical direction for the data engineering team and own the strategy, maintenance, and operations of our data platform. You’ll lead a team of data engineers while staying hands-on with architecture decisions and technical leadership. A key focus will be maintaining and building feature stores and ML infrastructure to power our machine learning models, enabling personalized experiences for millions of healthcare professionals.

Requirements

7+ years of professional experience in data engineering or software engineering, with 2+ years in a leadership or management role
Proven experience designing and operating data platforms at scale
Strong experience with 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)
Track record of mentoring engineers and building high-performing teams
Strong communication skills with the ability to translate technical concepts for non-technical stakeholders