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Lead Analytics Engineer - Data Modeling & Quality

Arcadia · Remote (USA) · Remote

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About the role

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.

What they're looking for

  • Advanced SQL: window functions, complex CTEs, aggregation patterns, performance tuning on columnar databases
  • DBT: hands-on experience authoring models, tests, macros, and yml documentation, familiarity with incremental strategies
  • Healthcare data literacy: working knowledge of claims data (professional, institutional, pharmacy), clinical data (EHR entities), and common quality dimensions (member months, coverage rates, null patterns)
  • Data quality mindset: ability to differentiate source data issues from transform issues, design systematic validation checks, and communicate data quality findings clearly
  • Clear communicator — able to translate technical findings for clients and non-technical stakeholders
  • Strong analytical judgment — you can look at a distribution and know when something is wrong
More 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...

Read the full posting on Arcadia's site ↗

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