Senior / Principal Data Infrastructure Engineer
Core
Design, build, and own the data systems that make proteomics data discoverable, trustworthy, and usable across the organization to support machine learning tools and experimental platforms.
Role type
Senior / Principal Data Infrastructure Engineer (hands-on IC)
Builds
Production-grade data platforms, automated workflows, and cloud infrastructure for biological and proteomics data processing.
Domain
Life Sciences / Biotechnology / Proteomics / Machine Learning
Deliverable
production ML models
Required skills
Cloud infrastructure (AWS, Azure), Kubernetes, Infrastructure as Code (Terraform, CDK, CFN), Data modeling (Postgres, Redshift, Snowflake), Data pipeline architecture (Flyte, Dagster, Airflow), Python, SQL, R, DevOps, CI/CD
Preferred skills
LLMs and agentic tooling, Mass spectrometry and NGS data sets, LIMS integration, Laboratory automation systems integration
Technologies
AWS, Azure, Kubernetes, Terraform, CDK, CFN, ARM, Postgres, Redshift, Snowflake, Delta Lake, Iceberg, Flyte, Dagster, Airflow, Dotmatics, Python, SQL, R
Responsibilities
Architect and build core data platforms integrating experimental proteomics data; Define and drive the technical roadmap for data infrastructure; Build automated workflows across research environments and integrate instruments and LIMS; Develop and operate robust data pipelines using workflow orchestration tools; Design, deploy, and maintain cloud-based infrastructure for data processing and storage; Establish and implement rigorous standards for data integrity, lineage, and traceability; Partner with scientists to translate objectives into data infrastructure solutions; Set engineering standards and mentor engineers and scientists.
Seniority
Senior / Principal, hands-on IC
