Mid-Level Platform Engineer, Biotech Clera · San Francisco · Platform & Infrastructure $180,000–$240,000 4d ago

Devopsroles; San Francisco (CA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Devopsroles is seeking a platform and data infrastructure engineer to build and operate the cloud data stack for our AI-focused biotech startup. You will enable scientists and ML engineers to access reliable, model-ready datasets and deploy data and models into partner environments.

You will own Kubernetes clusters, data warehousing, and reproducible bioinformatics workflows with Nextflow and containerized cloud compute, enforce data quality and security, and drive cost optimization across CI/CD

Qualifications

• 2–5 years building data infrastructure and production pipelines in biotech or health data.
• Experience with Kubernetes, Terraform, CI/CD, and deploying data pipelines.
• Strong Python and/or Go programming with clean, tested code.
• Experience with AWS and large-scale data pipelines.
• Familiarity with Nextflow, Docker, lakehouse/warehouse design.
• HIPAA/GDPR/SOC 2 controls knowledge; SQL knowledge helpful.

Responsibilities

• Build and maintain cloud data infrastructure, including Kubernetes clusters and data catalogs.
• Design and operate data warehouses and lifecycle processes for clinical data.
• Develop reproducible bioinformatics workflows using Nextflow and containerized compute.
• Build data quality checks and visualizations to identify issues.
• Create interfaces for preparing model-training datasets and delivering data to partners.
• Own reliability, observability, security, governance, and cost optimization, including CI/CD.

Skills

Python

Go

R

SQL

Tools

Kubernetes

Terraform

CI/CD

Nextflow

Docker

AWS

Job description

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.