Data Engineer-QNXT | USC Only.
About The Position
We are seeking a Data Engineer with expertise in Snowflake, AWS, and QNXT to design, build, and optimize scalable healthcare data platforms and analytics solutions. The role focuses on developing end-to-end data pipelines, integrating healthcare data from QNXT, and enabling reporting, analytics, and operational insights through modern cloud technologies. Key deliverables include QNXT data integration and migration, Snowflake data warehouse development, AWS-based data pipelines and automation, claims, membership, and provider data processing, and data quality and reconciliation frameworks.
Requirements
- At least 5 years of Data Engineering experience.
- Hands-on experience with Snowflake.
- Hands-on experience with AWS services, including S3, Lambda, Glue, Redshift, EMR, and Step Functions.
- Experience with SQL and data modelling.
- Experience with Python or Spark.
- Experience developing ETL/ELT workflows.
- Experience working with QNXT healthcare platforms and claims, eligibility, provider, and membership data.
- Strong understanding of data warehousing concepts and best practices.
- Experience with CI/CD, version control, and agile development methodologies.
- Resume must include a valid LinkedIn profile link; applications without one will not be considered.
- USC Only.
Nice To Haves
- Healthcare domain experience, particularly in Payer or Managed Care environments.
- Experience with data orchestration tools such as Airflow or AWS-native services.
- Knowledge of HIPAA and healthcare data compliance requirements.
- Exposure to Power BI, Tableau, or other BI platforms.
Responsibilities
- Design, develop, and maintain scalable data pipelines using AWS and Snowflake.
- Ingest, transform, and integrate healthcare and claims data from QNXT and related source systems.
- Build and optimize ETL/ELT workflows for large-scale data processing.
- Develop and maintain Snowflake data models, schemas, and data marts.
- Ensure data quality, governance, security, and compliance across the data lifecycle.
- Collaborate with business, analytics, and reporting teams to deliver trusted datasets and insights.
- Support performance tuning, monitoring, and troubleshooting of data platforms and pipelines.
- Implement data validation, reconciliation, and automation processes.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
