Data Engineer - Snowflake/AWS
First seen by Alion on Oct 19, 2026.
Role Summary :
We are seeking a skilled Data Engineer with expertise in Snowflake, AWS, and QNXT to design, build, and optimize scalable healthcare data platforms and analytics solutions. The ideal candidate will have strong experience developing end-to-end data pipelines, integrating healthcare data from QNXT, and enabling reporting, analytics, and operational insights through modern cloud technologies.
Key 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.
Required Skills :
- 5+ years of Data Engineering experience.
- Strong hands-on experience with :
1. Snowflake
2. AWS (S3, Lambda, Glue, Redshift, EMR, Step Functions)
3. SQL and Data Modelling
4. Python or Spark
5. ETL/ELT Development
- Experience working with QNXT healthcare platforms, 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.
Preferred Skills :
- Healthcare domain experience, particularly 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.
Skills
Data Engineering, Snowflake DB, AWS, QNX, ETL, Python, Spark, SQL, Data Modeling, Data Warehousing, Data Quality