Biomedical Data Platform Lead – Digital Pathology & WSI

PathAI; Oregon; Hybrid; USD 109,000 - 167,000; Full time

Job summary

PathAI, Inc. in Boston, MA seeks a Staff Biomedical Data Manager to drive governance and architecture for large-scale multimodal datasets, including whole slide imaging.

You will own the data platform roadmap and ensure data integrity across clinical programs, interfacing with leadership to standardize processes. The role requires strong experience in biomedical data management, data wrangling, ETL pipelines, and modern tooling (Python/R, Spark, Airflow, Databricks, Docker).

Qualifications

• Bachelor’s degree in Biomedical Informatics, Biomedical Engineering, Public Health, Epidemiology or related field plus 3 years of experience.
• Two years in Python or R for large-scale data wrangling, modeling and reporting; ETL/ELT pipelines; data governance.
• One year each in digital pathology workflows, CI/CD for data, oncology data, and handling sensitive datasets.

Responsibilities

• Define governance for clinical and translational datasets and scale data platforms.
• Own end-to-end data management, quality strategy, and scalable workflows for multi-modal data.
• Lead technical standards, documentation, and cross-functional training for data teams.
• Architect data models and tools for WSI data ingestion, storage, and metadata extraction.
• Drive roadmap for data platform evolution with senior leadership and partners.

Skills

Python

R

ETL pipelines

Data governance

CI/CD

Docker

Airflow

Databricks

Spark

GitHub Actions

Education

Bachelor's degree in Biomedical Informatics/related field

Master's degree +2 years experience

Tools

Spark

Airflow

Databricks

GitHub Actions

Docker

Job description

PathAI, Inc. in Boston, MA seeks a Staff Biomedical Data Manager to drive governance and architecture for large-scale multimodal datasets, including whole slide imaging.

You will own the data platform roadmap and ensure data integrity across clinical programs, interfacing with leadership to standardize processes. The role requires strong experience in biomedical data management, data wrangling, ETL pipelines, and modern tooling (Python/R, Spark, Airflow, Databricks, Docker).