Lead Analytics Engineer - Data Modeling & Quality

About this role

Arcadia is dedicated to happier, healthier days for all. We believe that there is a better healthcare world – one powered by data. Our platform transforms complex, diverse data into a unified foundation for health, helping organizations deliver better care, boost revenue, and lower costs.


We’re a team of fiercely driven individuals committed to making healthcare more sustainable—and we’re looking for passionate people to help us get there.


For more information, visit arcadia.io .


Why This Role Is Important to Arcadia
Arcadia's data platform powers population health analytics for health plans, ACOs, and provider groups across the country. As a Lead Analytics Engineer — Data Modeling & Quality, you sit at the intersection of data quality ownership and analytical data modeling. You'll own the SQL and dbt layer that transforms raw clinical and claims data into trusted, production-grade datasets, while also serving as the quality authority for the data those models produce.


This is a hybrid role — deeper SQL and dbt expertise than a traditional Data Health Professional, with a more analytical and model-focused scope than a Data Engineering role. You're less focused on pipeline infrastructure and more on the logic, shape, and trustworthiness of the data itself.


What Success Looks Like
In 3 months

• Independently triage and resolve pipeline data quality issues
• Author at least one new dbt model or refactor an existing one to meet current modeling standards
• Design a dbt test suite for a set of models lacking coverage
• Understand the end-to-end pipeline from ingress through silver and gold, and be able to trace a data quality issue to its root layer

In 6 months

• Building strong working relationships with clients and cross-functional partners (Data Engineering, Customer Success)
• Deeply familiar with Arcadia's full data stack — from ingress through silver, gold, and downstream consumers
• Driving at least one improvement ...