Bio Data Platform Engineer: Pipelines & Provenance

Outpost Bio; Boston (MA); On-site; USD 115,000 - 130,000; Full time

Benefits offered by this job

Equity

Comprehensive benefits

ML Lab-in-the-Loop

Flexible hours

Remote or partial remote availability

Job summary

Outpost Bio is hiring a Data Platform Engineer in Boston to build and operate pipelines that turn raw data into analysis-ready datasets. You will bridge the wet lab, CROs, and ML teams, ensuring traceability and reliability of training/inference runs on AWS.

We value 3–5 years experience building production data infra in Python, with strong engineering discipline and knowledge of orchestration tools (Dagster, Airflow, Prefect). Strong collaboration with scientists is essential.

Qualifications

• 3–5 years building and operating production data infrastructure.
• Team with strong engineering practices: code review, testing, deployment.
• Familiarity with Dagster, Airflow or Prefect and AWS compute (Batch/Fargate/S3).
• Able to translate scientist needs into robust, maintainable pipelines.
• Nice to have: omics or biology-related data experience.

Responsibilities

• Build and operate data pipelines turning raw data into analysis-ready datasets.
• Own datasets: schema, validation, provenance, versioning and documentation.
• Collaborate with wet-lab, CROs, and computational biology/ML teams.
• Maintain good engineering practices: reviews, tests, CI, diagnosable failures.
• Make training and inference runs traceable via versioned inputs and configurations.

Skills

Python

Data pipelines

CI/CD

Data infrastructure

Stakeholder communication

Tools

Dagster

Airflow

Prefect

AWS Batch

AWS Fargate

S3

Job description

Outpost Bio is hiring a Data Platform Engineer in Boston to build and operate pipelines that turn raw data into analysis-ready datasets. You will bridge the wet lab, CROs, and ML teams, ensuring traceability and reliability of training/inference runs on AWS.

We value 3–5 years experience building production data infra in Python, with strong engineering discipline and knowledge of orchestration tools (Dagster, Airflow, Prefect). Strong collaboration with scientists is essential.