Vanna Health

Data Engineer

• Own the infrastructure and platform supporting data jobs, including compute choices, orchestration, deployment, connectivity, reliability, and observability
• Set technical direction, make architecture decisions, write design documentation, and make build-versus-buy decisions
• Shape the data platform roadmap, own delivery, and communicate progress, risks, and trade-offs
• Establish design and code-review standards, mentor engineers, and unblock platform contributors
• Own Databricks and AWS platform architecture, including ingestion, storage, compute, access control, and environments
• Build tested, versioned connections to payer claims, eligibility, attribution, clinical, event, and care-platform systems over SFTP, S3, private networking, FHIR, and HL7
• Optimize job performance and cost through compute selection, right-sizing, serverless or cluster decisions, and migration from single-machine Python to distributed compute
• Own orchestration, deployments, Terraform, GitLab CI/CD, automated tests, and release practices
• Improve reliability and observability, detect failures and anomalies early, and design recoverable operations
• Make governed data usable by AI through metric definitions, Genie spaces, and MCP servers
• Validate incoming data using row counts, date spans, expected fields, and historical coverage
• Automate recurring data operations and participate in a shared, lightweight data operations rotation
• Protect PHI through access controls, auditing, de-identification, and secure data exchange
• Provide analytics engineering with a reliable, timely, cost-effective platform
• Represent data engineering with partners, vendors, and colleagues and share knowledge

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Senior Data Engineer, Platform