Mid-Level Platform Engineer, Biotech

Clera

San Francisco, CA

On-site

Who this role is best for

Platform engineers with biotech or health data experience and cloud infrastructure expertise will find this hybrid role in San Francisco emphasizes data reliability and compliance.

Best fit for

Candidates with 2-5 years of data infrastructure experience in biotech or health data domains
— “Two to five years building data infrastructure and production pipelines, with experience in biotech, diagnostics, biobanking, or health data involving sensitive or biological information.”
Professionals skilled in Kubernetes, Terraform, and CI/CD systems for cloud environments
— “Production experience building and operating Kubernetes clusters, writing infrastructure as code with Terraform or similar tools, and designing CI/CD and deployment systems.”
Individuals with a track record in reproducible bioinformatics workflows and omics data processing
— “Develop reproducible bioinformatics workflows for omics data, using workflow managers such as Nextflow and containerized cloud compute.”

Things to consider

Visa sponsorship is not available, which may limit non-US candidates’ eligibility
— “Visa sponsorship is not available.”
The role requires a hybrid work arrangement based in San Francisco
— “Hybrid role based in San Francisco, California.”

How to stand out

Highlight experience with HIPAA, GDPR, or SOC 2 compliance in your resume and interviews
— “Knowledge of controls and audit practices for HIPAA, GDPR, or SOC 2 is beneficial.”
Emphasize your ability to design secure, scalable data warehouses and lifecycle processes
— “Design and operate data warehouses and lifecycle processes for clinical records, molecular features, metadata, and versioned dataset releases.”

Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

Build and maintain cloud data infrastructure for sensitive clinical and biomedical data

Typical background

2-5 years building data infrastructure and production pipelines

Skills & requirements

Required

KubernetesTerraformPythonGoAWSDockerNextflowOMOPFHIR

Preferred

GPUMachine Learning InfrastructureDistributed TrainingOmics Workflows

Stack & domain

KubernetesTerraformPythonGoAWSDistributed Job OrchestrationLarge-scale Data PipelinesLakehouse And Warehouse DesignDockerWorkflow ManagersGPUMachine Learning InfrastructureDistributed TrainingOmics WorkflowsClinical Data StandardsHIPAAGDPRSOC 2RSQLBiotechDiagnosticsBiobankingHealth DataSensitive DataBiological Data

About the role

Original posting from Clera via Ashby

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.

Source: Clera careers (Ashby)