Analytics Engineer

About the role

Join Counsel Health as an Analytics Engineer, where you will own the semantic layer of our data, build and maintain core analytics data models, and ensure data compliance. You will have significant opportunities for broad ownership and professional development, along with a comprehensive benefits package. Key missions: Posséder la couche sémantique : construire et maintenir des modèles de données qui définissent nos indicateurs commerciaux clés.. Orchestrer et surveiller : exécuter l'orchestration dbt avec des alertes intégrées, des pipelines CI/CD et des tests de qualité des données.. Construire des pipelines Reverse ETL : mettre en place les flux de données qui alimentent des données propres et modélisées dans les systèmes de production. Profile: - 3+ years of experience in analytics engineering, data analytics, or a hybrid data role - Experience with data orchestration tooling (Paradigm, dbt Cloud, Airflow, or similar), and integrating analytics data back into production systems - Experience working in a regulated industry (healthcare, fintech, insurance, government) with proven ability to manage sensitive data and access controls. HIPAA familiarity is a plus - Experience with BigQuery or comparable cloud data warehouses (Snowflake, Redshift) - Deep expertise in SQL and dbt - A Context Engineer: You think in business entities and stakeholder questions, not just tables and joins. You translate fuzzy requirements into clean, well-modeled data - Infrastructure-Comfortable: You're not a data engineer, but you can manage orchestration, environments, and reverse ETL pipelines without hand-holding - Product-Minded: You don't just model data — you ask why someone needs it and how it drives a patient or business outcome - Thrives in Ambiguity: We're a fast-moving company with evolving data needs. You feel energized by creating structure in ambiguous environments, and you are comfortable synthesizing needs from multiple stakeholders into a clear data strategy - Dbt + SQL Native: dbt is your primary tool. You write clean, modular, well-tested transformations and you have strong opinions about how a dbt project should be organized