Data Engineer - Snowflake Data Integration & Data Platform

iSpace Inc
Clayton, MO, United States
26 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$137,280.0
Working hours
Regular working hours
Job source

Tech stack

Microsoft Excel Agile Methodology Amazon Web Services Amazon S3 Data Analysis Batch Processing Cloud Computing Continuous Integration Data Validation Information Engineering Data Governance Data Integration
+23 more
Extract Transform Load (ETL) Data Mapping Data Structures Database Development DevOps File Systems Executive Information Systems Data Intelligence Python (Programming Language) Meta-Data Management Performance Tuning Power BI Software Deployment SQL Stored Procedures Data Streaming System Integration Testing Talend Planning Software Data Processing Data Ingestion Snowflake Integration Frameworks Control M

Job description

  • 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.

Data Engineering & Snowflake Development

  • 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.

Data Modeling

  • 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.

Data Quality & Governance

  • 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.

Project Delivery Support

  • 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., Expected Deliverables
  • 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

Business Value 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.

Requirements

  • 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 DevOps Practices

Integration Platforms 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)

Preferred Skills

  • 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

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