Senior Data Engineer - Snowflake

Title:
Senior Data Engineer - Snowflake Data Integration & Data Platform

Location:
Clayton, MO (REMOTE)

Duration: 12 Months

Pay rate $66 Per hr on W2

• Design and develop automated ingestion pipelines for Excel, CSV, and structured source files.
• Implement Snowpipe and Snowpipe Streaming solutions for real-time and batch processing.
• Configure external stages and ingestion frameworks utilizing AWS S3 and Snowflake.
• Develop scalable ELT/ETL solutions using Python, Talend, or Informatica IDMC.
• Build metadata-driven ingestion processes supporting future onboarding of new source systems.

• Design Raw, Curated, Workflow, Audit, and Reporting layers within Snowflake.
• Create ingestion monitoring, exception handling, and automated restart capabilities.
• Develop stored procedures, tasks, streams, and orchestration workflows.
• Implement file-level auditing, reconciliation controls, and data validation frameworks.
• Optimize Snowflake performance, clustering, and storage utilization.

• Design dimensional, relational, and reporting data models.
• Create fact and dimension structures supporting operational workflows and Power BI dashboards.
• Develop audit history and event-based data structures supporting regulatory traceability.
• Define logical and physical data models aligned with business requirements.

• Implement source-to-target mapping documentation.
• Create automated data quality controls and exception reporting.
• Develop reconciliation processes between source files and Snowflake datasets.
• Support enterprise data governance standards, metadata management, and lineage requirements.
• Establish audit-ready controls supporting regulatory compliance needs.

• Participate in requirements analysis and technical design sessions.
• Support System Integration Testing (SIT), User Acceptance Testing (UAT), and production deployments.
• Collaborate with UI developers, Power BI developers, business analysts, and business stakeholders.
• Produce technical documentation, operational procedures, and support guides.

• Snowflake Data Engineering (Advanced)
• Snowpipe and Snowpipe Streaming
• Snowflake Tasks, Streams, Stored Procedures, and Stages
• Python Development
• SQL Development and Performance Tuning
• AWS S3 Integration
• Data Modeling (Dimensional and Relational)
• ETL/ELT Development
• Data Quality Frameworks
• Source-to-Target Mapping
• CI/CD and Dev Ops Practices

Candidate should possess expertise in one or more of the following:

• Informatica Intelligent Data Management Cloud (IDMC)
• Talend Data Integration
• Python-based data engineering frameworks
• Control M or enterprise scheduling platforms (preferred)

• Healthcare Data and Analytics Experience
• Medicare Risk Adjustment Experience
• RADV Audit Data Processing Experience
• CMS Data Submission Experience
• Power BI Data Modeling Support
• AWS Cloud Services
• Data Governance and Metadata Management
• Agile Delivery Methodologies

• End-to-end Snowflake ingestion framework
• Automated Excel and CSV ingestion processes
• Snowpipe-based file processing solution
• Source-to-target mapping documentation
• Snowflake Raw, Curated, and Reporting data layers
• Data quality and reconciliation framework
• Data model documentation
• Production deployment package
• Operational support runbooks
• Monitoring and alerting framework

This resource will:

• Accelerate delivery of the RADV Audit Tool 2.0 data platform.
• Enable automated ingestion of CMS, Optum, CDAT, and audit workflow data into Snowflake.
• Reduce manual processing effort through scalable and reusable ingestion patterns.
• Improve data quality, audit traceability, and regulatory compliance.
• Establish a reusable enterprise ingestion framework for future Risk Adjustment initiatives.
• Provide a high-quality data foundation supporting workflow applications, Power BI reporting, operational monitoring, and executive dashboards.
• Support the aggressive January 25, 2027 production deployment timeline by providing dedicated expertise in Snowflake architecture, ingestion automation, and data engineering.