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About the Role
Join a biotech AI team building data infrastructure that turns clinical, genomic, imaging, and other biomedical data into reliable, model-ready assets. You will help design and operate the platform, with a focus on secure, governed data systems and production infrastructure for scientific and machine learning teams.
Responsibilities
- Build and maintain cloud data platform components, including object storage, lakehouse architecture, catalogs, lineage, dataset versioning, and query and access layers.
- Design and operate data warehouses and governed systems for clinical records, molecular features, metadata, retention, and dataset releases.
- Develop reproducible bioinformatics workflows for omics data, using containerized pipelines and cloud batch compute.
- Implement data quality checks, biological validation, and visualizations that help teams identify issues across processing steps.
- Deliver versioned, training-ready datasets and data deployment interfaces for model use in partner environments.
- Operate production infrastructure, including Kubernetes, CI/CD, workload orchestration, security, reliability, observability, and cost optimization.
Requirements
- Two to five years of experience building data infrastructure and production pipelines as a platform engineer in biotech, diagnostics, biobanking, health data, or a related field working with sensitive biological or clinical data.
- Production experience operating Kubernetes clusters, writing infrastructure as code with Terraform or similar tools, and shipping tested, documented Python and/or Go code.
- Experience designing CI/CD and deployment systems, orchestrating distributed workloads, and owning infrastructure reliability, observability, security, and cost.
- Familiarity with a major cloud provider, preferably AWS, plus Docker, workflow managers such as Nextflow, lakehouse and warehouse design, data catalogs, and orchestration.
- Experience with large-scale data pipelines, machine learning infrastructure, or GPU workloads is valuable.
- Knowledge of omics workflows, bioinformatics tools, OMOP, FHIR, R, or SQL is also relevant.
- Experience implementing compliance controls and audit evidence for standards such as HIPAA, GDPR, or SOC 2 is beneficial.
Skills
- Kubernetes
- Terraform
- Python
- Go
- CI/CD
- AWS
- Docker
- Nextflow
- Lakehouse architecture
- Data catalogs
- Omics workflows
- Bioinformatics tools
- OMOP
- FHIR
- R
- SQL
- HIPAA
- GDPR
- SOC 2
Location
- San Francisco, California
Work Type
- Hybrid
Experience Level
- 2-5 years
Salary/Compensations
- $180,000 to $240,000