via Dice
$120K - 200K a year
Transform raw healthcare data into scalable, production-grade datasets using dbt and SQL, collaborating with stakeholders to meet business needs.
Deep knowledge of healthcare claims and membership data, expert SQL and dbt skills, proficiency in cloud data warehouses like Snowflake, and experience with data modeling and orchestration tools.
Lead Analytics Engineer: Healthcare Claims, SQL & dbt Location: Remote Duration: 12+ Months Client: 10 Pearls / Cohere Health Job Summary We are seeking a Senior Analytics Engineer with deep expertise in Healthcare Claims and Membership data to architect and optimize the transformation layers for a modern data platform. This role sits at the intersection of Data Engineering and Business Intelligence, where you will be responsible for taking raw healthcare data and modeling it into production-grade, modular datasets using dbt and SQL. You will act as a consultant to non-technical stakeholders including Actuaries and C-Suite teams to translate complex business requirements into scalable dimensional models within a Cloud Data Warehouse (Snowflake, BigQuery, or Redshift). Key Responsibilities & Required Skills Healthcare Data Transformation & Modeling Claims & Membership Expert: Transform raw payer data, claims, and membership records into usable formats for end-user analytics. Dimensional Modeling: Architect modular dbt models, dimensional structures, and semantic layers to standardize metrics across the organization. Stakeholder Collaboration: Partner with Actuaries and Business Analysts to gather requirements and design data solutions that drive business value. Production-Grade Analytics Engineering dbt Mastery: Build, test, and optimize dbt models (Core or Cloud) using engineering best practices like CI/CD and Git. Advanced SQL: Develop high-quality SQL transformations and reusable datasets focused on performance optimization. Data Quality: Implement rigorous testing frameworks, validation logic, and lineage visibility to ensure "trusted data" for the ecosystem. Cloud Infrastructure & Orchestration Cloud Data Warehouse: Hands-on experience with Snowflake, BigQuery, or Redshift for large-scale healthcare data processing. Orchestration: Familiarity with tools like Airflow, Dagster, or Prefect to schedule and operationalize transformation pipelines. Modern Stack: Utilize AWS environments and modern software development workflows to manage data discoverability and reliability. Mandatory Technical Skills 1. Healthcare Data Experience: Deep knowledge of Payer/Claims/Membership data. 2. Expert SQL & dbt: Proven experience building modular, production-grade pipelines. 3. Data Modeling: Expertise in dimensional modeling and semantic layer design. 4. Cloud Warehouse: Proficiency in Snowflake, BigQuery, or Redshift. Thanks, Aditya Jain | New York Technology Partners Email: Direct: EXT: 482
This job posting was last updated on 1/8/2026