End-to-End Data Platform Engineer for Neuroscience Pipelines

Stanford University School of Medicine; Palo Alto (CA); Presencial; USD 140.000 - 210.000; Jornada completa

Descripción de la vacante

Stanford University School of Medicine is seeking a Data Engineer to design, build, and maintain the data platform supporting Enigma’s experimental workflows. You will move raw data from acquisition through ETL/ELT transformations into downstream stores, shaping lakehouse schemas and ensuring governance and observability.

You will partner with scientists and engineers to deliver reliable systems, own data interfaces end-to-end, and optimize performance across storage, compute, and networks while

Formación

• Bachelor's degree with five years of relevant experience or equivalent.
• Strong proficiency in Python and SQL.
• Experience with relational and NoSQL databases and object storage.
• Production ETL/ELT pipeline design and operation.
• Durable data models and schemas for evolving datasets.
• High-throughput data ingestion and optimized data movement.
• Experience with API design and service interfaces.

Responsabilidades

• Design, build, and operate ETL/ELT pipelines and high-throughput ingestion systems.
• Own the data layer end-to-end: schema design, indexing, migrations, backups, durable models.
• Improve reliability, scalability, observability, and performance across the data stack.
• Build tools to help researchers discover datasets, inspect state, and rerun jobs.
• Productionize research code with testing, packaging, deployment, and monitoring.
• Collaborate with data acquisition, infra, scientific analysis, and AI modeling teams.

Conocimientos

Python

SQL

Data modeling

APIs

Cross-functional collaboration

Production ETL/ELT pipelines

Data governance

Snowflake/BigQuery

Educación

Bachelor's degree

Herramientas

Docker

Kubernetes

Airflow

Dagster

Prefect

Descripción del empleo

Stanford University School of Medicine is seeking a Data Engineer to design, build, and maintain the data platform supporting Enigma’s experimental workflows. You will move raw data from acquisition through ETL/ELT transformations into downstream stores, shaping lakehouse schemas and ensuring governance and observability.

You will partner with scientists and engineers to deliver reliable systems, own data interfaces end-to-end, and optimize performance across storage, compute, and networks while