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Eon Health is seeking a Data Engineer to design and maintain the data infrastructure powering their healthcare platforms and products. The company's mission is to make patients healthier and healthcare affordable through AI-enabled patient management solutions.
In this role, you will design, build, and maintain robust ETL/ELT pipelines for ingesting, transforming, and standardizing healthcare data from diverse sources including EHRs, wearable devices, and claims systems. You'll ensure data quality, privacy, and compliance with healthcare regulations such as HIPAA and GDPR. Working cross-functionally with product managers, data scientists, clinical experts, and software engineers, you'll deliver data solutions that support analytics and clinical decision-making.
Key responsibilities include developing and optimizing cloud-based data infrastructure and warehouses (AWS RDS, Snowflake), maintaining secure and scalable data models for internal and external use, monitoring pipeline performance, troubleshooting issues, and continuously improving data reliability. You'll stay current with data engineering best practices and evolving healthcare data standards like FHIR and HL7.
This is a hands-on role that directly supports Eon's mission of delivering better healthcare through data. The company offers a dynamic, results-focused team environment with both local office presence in Glendale and remote work flexibility.
Qualifications and Requirements:
- 2–4 years of experience in a Data Engineering role, preferably in healthcare, biotech, or life sciences
- Strong SQL skills and experience with large-scale relational databases
- Proficiency in Python or similar language for data engineering tasks
- Experience with cloud platforms (GCP, AWS, or Azure) and data tools like Airflow or dbt
- Knowledge of data modeling, data warehouse design, and data integration patterns
- Understanding of healthcare data formats and standards (ICD-10, CPT, FHIR, HL7) is a strong plus
- Familiarity with data privacy, security protocols, and compliance frameworks (HIPAA, SOC 2)
- Strong problem-solving skills, attention to detail, and collaborative work style
- Experience with real-time data processing tools (SQL, Python, Airflow)
- Background supporting data needs for clinical research or healthcare analytics
- Familiarity with BI tools such as Looker, Tableau, or Power BI
- Exposure to MLOps or data science workflows
