Founding Senior Data Engineer

Geviti is a next-generation health optimization platform helping individuals take control of their health through advanced diagnostics, AI-driven insights, and personalized care. Our members benefit from custom lab panels, continuous biomarker tracking, wearable integration, and tailored interventions—including hormone optimization, peptide therapies, supplements, and evidence-based lifestyle strategies.

We’re setting a new standard in proactive, precision-based care—designed not just to treat illness, but to optimize health and longevity. Technology and data are at the heart of how we deliver this vision, powering everything from personalized member experiences to real-time operational insights and AI-driven clinical intelligence.

We are searching for a Senior Data Engineer to serve as the founding member of our data function. You will architect the core data infrastructure that supports every part of the business—from clinical operations to member experience to AI-powered insights.

You’ll build our data pipelines, warehouse/lakehouse environment, workflow orchestration, and foundational data models. As the organization’s first dedicated data engineering hire, you’ll operate with a high degree of autonomy, influence technical direction, and enable advanced downstream use cases including analytics, BI, and machine learning.

This is a hands-on, high-impact role ideal for someone excited to design a system from the ground up and shape the future of data at Geviti.

• 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
• Evaluate tooling for orchestration, workflow automation, and observability
  

• 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
• Ensure PHI and HIPAA-compliant data access, storage, and transmission practices

• Collaborate with analytics and product teams to build source-of-truth datasets and KPI reporting layers
• Partner with engineering to instrument data collection and event tracking across the platform
• Enable self-service analytics by delivering clean, well-modeled data assets and clear documentation

• Build pipelines and data structures that support machine learning training, testing, and deployment
• Prepare datasets for AI-driven features, RAG workflows, and real-time personalization
• Support experimentation frameworks, A/B testing, and future intelligent system capabilities

• Work closely with product, engineering, operations, and clinical teams to understand data needs and deliver scalable solutions
• Uphold HIPAA and best practices for secure PHI handling across all data environments
  

• 5+ years of experience as a Data Engineer or similar data infrastructure-focused role
• Expert SQL proficiency, including schema design, warehouse modeling, and query optimization
• Strong Python experience for ETL/ELT development, automation, and data processing
• Proven experience architecting and maintaining cloud-based data warehouse/lakehouse environments (e.g., Snowflake, BigQuery, Redshift, Databricks)
• Deep knowledge of ETL/ELT frameworks, workflow orchestration (Airflow, dbt, Prefect, Dagster), and data quality methodologies
• Experience with API integrations, event-based data flows, and data modeling for analytics
• Familiarity with modern BI ecosystems and supporting high-quality reporting layers

• Deep statistical foundation and experience designing experiments
• Ability to translate ambiguous business challenges into measurable data solutions
• Experience with product and customer analytics
• Strong communication skills—able to make data meaningful for non-technical stakeholders
• Self-starter mindset with comfort operating independently and building systems from the ground up
• Strong systems-thinking approach with attention to reliability, performance, and cost
• Excellent documentation and communication skills
• Highly autonomous, proactive, and comfortable building systems from the ground up

• Experience in healthcare or healthtech environments
• Knowledge of FHIR standards or healthcare data models
• Familiarity with HIPAA compliance and secure data handling
• Exposure to ML frameworks (classification, regression, time-series, RAG)
• Cloud certifications or real-time analytics experience
• Prior experience as a founding or first data hire

• Work on meaningful problems that directly improve people’s health and longevity
• Join a mission-led, growth-oriented team shaping the future of healthcare
• Competitive compensation with opportunities for leadership and growth
• Build impactful products at the intersection of health, data, and AI