Data Platform Engineer — Equity & ML-Driven Pipelines

Outpost; Greater London; Hybrid; GBP 75,000 - 85,000; Full time

Benefits offered by this job

Equity

Private medical

Dental (Bupa)

Pension 3%

Life insurance

Income protection

Cycle to Work

25 days holiday + bank holidays

Job summary

Outpost Bio is seeking a Data Platform Engineer to build and operate data pipelines and own the datasets that pipelines produce. The role sits between the wet lab CROs and the computational biology/ML teams, running orchestration on cloud compute for CRO deliveries and lab cycles.

The engineer will ensure traceable training/inference runs, maintain good engineering practices, and contribute to reliable data infrastructure in a fast-moving biotech environment.

Qualifications

• 3–5 years building production data infrastructure using Python.
• Experience owning pipelines used by others and handling failures.
• Familiar with workflow orchestrators (Dagster/Airflow/Prefect) and AWS compute.
• You can work from a spec and call out gaps rather than implementing blindly.
• You can discuss data generation with scientists and separate constraints from preferences.
• You are motivated by reliability and maintainability.

Responsibilities

• Build and operate pipelines that turn raw data into analysis-ready datasets.
• Own the datasets: schema stability, validation, provenance, versioning, and transformation.
• Collaborate with wet lab CROs and ML teams to understand data use and constraints.
• Maintain engineering practices: code reviews, tests, CI, and observable failures.
• Ensure traceability of training/inference runs with versioned inputs and config.

Skills

Python

Data pipelines

Dagster

Airflow

Prefect

AWS

CI/CD

Testing

Documentation

Communication

Tools

Dagster

Airflow

Prefect

AWS

Terraform

dbt

SQL

ClickHouse

DuckDB

S3

Job description

Outpost Bio is seeking a Data Platform Engineer to build and operate data pipelines and own the datasets that pipelines produce. The role sits between the wet lab CROs and the computational biology/ML teams, running orchestration on cloud compute for CRO deliveries and lab cycles.

The engineer will ensure traceable training/inference runs, maintain good engineering practices, and contribute to reliable data infrastructure in a fast-moving biotech environment.