Data Engineer Revenue Cycle Management

We are seeking a Data Engineer to support the development and maintenance of scalable data infrastructure and analytics solutions aligned with strategic business goals.

This role focuses on building reliable data pipelines, integrating healthcare revenue cycle data, and enabling downstream analytics and operational systems.

• Data Pipeline Development:
  Design, build, and maintain robust ETL/ELT pipelines using dbt, Python, and SQL to ingest and transform healthcare data from diverse sources.
• Cloud Data Engineering:
  Work within AWS and Snowflake environments to manage data storage, processing, and access for analytics and operational use cases.
• Collaboration:
  
  Partner with data scientists, analysts, and application developers to deliver clean, well-modelled data that supports AI/ML, reporting, and business intelligence.
• Healthcare Data Integration (Preferred):
  Develop solutions to integrate healthcare revenue cycle data (e.g., 835/837 files, claims, and denial data) into centralized data platforms.
• Data Quality and Governance:
  Implement data validation, lineage tracking, and governance practices to ensure accuracy, compliance, and traceability.
• Operational Enablement:
  Deliver curated datasets from Snowflake to support downstream systems such as Artiva, applications, and reporting tools.
• Continuous Improvement:
  Contribute to the modernization of legacy systems and participate in initiatives to unify data platforms across the organization.

• 2–5 years of experience in data engineering or a related field.
• Proficiency in SQL and moderate experience with Python for data transformation and automation.
• Hands-on experience with dbt and Snowflake.
• Experience working with cloud platforms, preferably AWS.
• Understanding of data modeling and cloud data architecture.
• Strong analytical and problem-solving skills.
• Effective communication and collaboration skills in cross-functional teams.
• Eagerness to learn and grow in a fast-paced, evolving data environment.

• Experience with healthcare data, especially revenue cycle management (e.g., 835/837 files).
• Familiarity with ETL tools, CI/CD workflows, and version control systems (e.g., Git Hub).
• Exposure to data governance and compliance frameworks (e.g., HIPAA).