Clarity on the Role:Wellvana is seeking an experienced Analytics Engineer to help build and scale the data infrastructure behind Clarity, our analytics platform for ACO/MSSP partners. This is a hands-on engineering role: you'll own dbt models, build and maintain Dagster pipelines, and work directly with claims and provider data across a growing partner network. You'll work closely with the data engineering team and CTO to turn CMS claims, vendor feeds, and internal source systems into reliable, well-modeled data that drives partner-facing analytics and internal decision-making.
What's Expected:- Design and build dbt models on Snowflake that answer real business and partner questions, not just pass through raw data
- Develop and maintain models within a medallion architecture (bronze/silver/gold), keeping raw, cleaned, and business-ready layers clearly separated and well-tested
- Build and maintain semantic layer definitions so metrics are consistent, documented, and reusable across dashboards and partner reporting
- Operate with and extend Dagster pipelines: ingestion, transformation, scheduling, and asset-level data quality checks
- Work with CMS claims data (CCLF, ALR) and provider hierarchy sources (NPI, TIN, CCN, PECOS/NPPES) to support ACO attribution and performance reporting
- Build and maintain vendor data-sharing pipelines (S3, Iceberg-format tables, SFTP) for external partners and vendors
- Investigate and resolve data anomalies across ingestion pipelines: row count drops, schema drift, upstream vendor changes
- Diagnose pipeline failures with a bias toward hard failures and root-cause fixes, not silent fallbacks or defensive workarounds that mask problems
- Collaborate with analysts and other engineers to keep data models understandable and well-documented
- Increasingly, work alongside AI coding agents (e.g., Claude Code) to accelerate pipeline development, code review, and documentation, and be comfortable with that shifting the shape of day-to-day engineering work over time
Requirements
What's Required:Education- Bachelor's or Master's degree in computer science, engineering, or a related field (equivalent experience considered
Years of Related Experience- 2-3 years of experience as an analytics engineer, data analyst, or similar role with hands-on SQL and dbt work; healthcare or claims data exposure a plus, not a requirement
Skills/Competencies/Behaviors- Strong SQL and data modeling skills, comfortable designing dbt models from source data, not just querying existing ones
- Production experience with dbt (models, tests, macros); exposure to an orchestrator (Dagster, Airflow, or similar) a plus
- Familiarity with medallion architecture patterns (bronze/silver/gold) and semantic layer concepts (metrics definitions, reusable business logic)
- Working proficiency in Python for data transformation and light tooling work
- Working knowledge of AWS (S3 basics) and comfort querying cloud data warehouses (Snowflake or similar)
- Interest in healthcare claims data (Medicare claims, CCLF, or similar) a plus; willingness to learn ACO/MSSP attribution logic
- Understanding of data governance and PII/PHI-aware data handling
- Comfort working with AI coding assistants as part of the standard workflow, not just as a novelty
- Strong troubleshooting instincts and a preference for surfacing problems early over papering over them
- Ability to work independently and communicate clearly with both technical and non-technical stakeholders
