Geviti

Data Engineer

• Architect, build, and maintain a scalable cloud-based data warehouse or lakehouse environment
• Design and implement robust ETL/ELT pipelines integrating data from clinical systems, internal tools, third-party APIs, and operational platforms
• Develop clean, well-structured data models optimized for analytics, reporting, and data science
• Implement data quality processes, validation layers, testing frameworks, and governance standards
• Create and maintain metadata documentation, data dictionaries, lineage tracking, and schema definitions
• Optimize warehouse performance, cost efficiency, and pipeline reliability
• Own end-to-end data ingestion processes ensuring stable, timely, and accurate data availability
• Establish monitoring, alerting, logging, and operational observability for all pipelines
• Troubleshoot and resolve data inconsistencies, ingestion failures, and system bottlenecks
• Collaborate with analytics and product teams to build source-of-truth datasets and KPI reporting layers
• Build pipelines and data structures that support machine learning training, testing, and deployment

Founding Senior Data Engineer