Mid-Level Platform Engineer, Biotech

About the Role Join the platform and data engineering team at an AI-focused biotech startup, building and operating infrastructure for sensitive clinical and biomedical data. Your work will help scientists and machine learning engineers access reliable, model-ready datasets and deploy data and models into partner environments. What You'll Do Build and maintain cloud data infrastructure, including Kubernetes clusters, object storage, lakehouse layouts, catalogs, lineage, versioning, and data access systems. Design and operate data warehouses and lifecycle processes for clinical records, molecular features, metadata, and versioned dataset releases. Develop reproducible bioinformatics workflows for omics data, using workflow managers such as Nextflow and containerized cloud compute. Build data quality checks, biological validation, and visualizations that help teams identify issues throughout processing. Create reliable, versioned interfaces for preparing model-training datasets and delivering data alongside models to partner environments. Own infrastructure reliability, observability, security, compliance controls, and cost optimization, including CI/CD and workload orchestration. What We're Looking For Two to five years building data infrastructure and production pipelines, with experience in biotech, diagnostics, biobanking, or health data involving sensitive or biological information. Production experience building and operating Kubernetes clusters, writing infrastructure as code with Terraform or similar tools, and designing CI/CD and deployment systems. Strong production programming skills in Python and/or Go, with clean, tested, well-documented code and effective code review practices. Experience with a major cloud provider, preferably AWS, distributed job orchestration, and large-scale data pipelines. Familiarity with lakehouse and warehouse design, data catalogs, Docker, and workflow managers such as Nextflow. Experience with GPU or machine learning infrastructure, distributed training, omics workflows, or clinical data standards such as OMOP and FHIR is valuable. Knowledge of controls and audit practices for HIPAA, GDPR, or SOC 2 is beneficial; R or SQL experience is also useful. Compensation & Benefits Salary range: $180,000 to $240,000 USD annually. Visa sponsorship is not available. Location Hybrid role based in San Francisco, California.