remote
Data Engineer, Synthetic Data Generation - Humana
Data Engineer
Design and deliver high‑quality synthetic healthcare member data using tools like GenRocket, handling end‑to‑end data pipelines, validation, and integration to support testing, analytics, and system integration.
About the role
Key Responsibilities
- Design, generate, and validate synthetic member datasets that reflect complex healthcare business rules and membership processes.
- Develop and maintain ETL pipelines for ingesting EDI feeds, transforming data, and loading it into downstream platforms.
- Utilize GenRocket and custom scripting (Python/SQL) to create realistic data scenarios for testing and analytics.
- Collaborate with business analysts, data scientists, and platform engineers to ensure synthetic data aligns with real‑world data models and compliance requirements.
- Implement automated data quality checks and monitoring to guarantee integrity, accuracy, and usability of generated data.
Requirements
- 2+ years of experience in data engineering, preferably in healthcare or related regulated domains.
- Proficiency in Python and SQL for data manipulation, transformation, and validation.
- Hands‑on experience building ETL pipelines and working with EDI or other structured data formats.
- Familiarity with synthetic data generation tools such as GenRocket or similar platforms.
- Strong understanding of healthcare data standards (e.g., HL7, X12) and data modeling concepts.