Data Engineer

What You ll Do

• Develop and maintain DBT models in Snowflake with proper testing and documentation
• Design and build Python data pipelines that are reliable, testable, and observable
• Orchestrate workflows using Argo-Workflows running on Kubernetes
• Transform raw source data into clean, well-modeled datasets for analysts and ML systems
• Manage and improve Azure cloud infrastructure using terraform
• Work on RAG pipelines and vector stores for AI agents
• Stay current with developments in applied AI and bring relevant innovations to the team
• Use tools like Claude Code and Cursor as part of your daily workflow
• Help establish team practices for effective human-AI collaboration in engineering

• 3+ years experience building production DBT or other SQL based transforms with testing, documentation, and CI/CD
• Experience working with python with an emphasis on readable, maintainable code
• Familiarity with Kubernetes and container orchestration
• Ability to communicate technical concepts clearly to diverse audiences
• Flexibility and willingness to wear many hats and help out wherever it is needed

• Early stage startup experience
• Analysis or analytics engineering experience
• Experience with AI prompt engineering and LLM application development
• Experience managing cloud infra such as Kubernetes clusters
• Familiarity with clinical and medical insurance claims data
• DBT for transformation workflows and data modeling
• Snowflake for data warehousing
• Python for data loading, tokenization, and manipulation (Pandas, Polars) and integration with our AI platform
• Data orchestration using Argo-Workflow DAGs
• Azure cloud infrastructure with Kubernetes

$130,000 - $170,000 per year
, based on experience

Benefits include: stock options, medical/dental/vision, and 401k

• Beat Yesterday – Continuous improvement, innovation, and growth
• Embrace Type 2 Fun – Resilience and positivity in the face of challenges
• Act Like an Owner – Initiative, accountability, and focus on outcomes
• Stay Hungry, Stay Curious – Humility, curiosity, and bold thinking

• Initial screen with our recruiters
• Phone screen with our head of engineering
• On-Site Interview Loop
• Technical interview focused on real-world problem solving (no whiteboard algorithms!)
• Behavioral interview to explore your approach to teamwork and challenges
• 1:1 with our PM
• Final loop with our Head of Engineering
• Final conversation with our CEO

If you re excited about solving complex data challenges in the benefits space while making a meaningful impact on businesses and their employees, we d love to hear from you!