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
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Build and maintain cloud data infrastructure, including Kubernetes clusters, object storage, lakehouse layouts, catalogs, lineage, versioning, and data access systems.
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Design and operate data warehouses and lifecycle processes for clinical records, molecular features, metadata, and versioned dataset releases.
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Develop reproducible bioinformatics workflows for omics data, using workflow managers such as Nextflow and containerized cloud compute.
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Build data quality checks, biological validation, and visualizations that help teams identify issues throughout processing.
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Create reliable, versioned interfaces for preparing model-training datasets and delivering data alongside models to partner environments.
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Own infrastructure reliability, observability, security, compliance controls, and cost optimization, including CI/CD and workload orchestration.
What We're Looking For
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Two to five years building data infrastructure and production pipelines, with experience in biotech, diagnostics, biobanking, or health data involving sensitive or biological information.
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Production experience building and operating Kubernetes clusters, writing infrastructure as code with Terraform or similar tools, and designing CI/CD and deployment systems.
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Strong production programming skills in Python and/or Go, with clean, tested, well-documented code and effective code review practices.
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Experience with a major cloud provider, preferably AWS, distributed job orchestration, and large-scale data pipelines.
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Familiarity with lakehouse and warehouse design, data catalogs, Docker, and workflow managers such as Nextflow.
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Experience with GPU or machine learning infrastructure, distributed training, omics workflows, or clinical data standards such as OMOP and FHIR is valuable.
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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.
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