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About Washington University in St. Louis
Washington University in St. Louis is a private research university known for excellence in medicine, law, business, engineering, and the arts, affiliated with one of the nation''s top medical schools. Industry: Higher Education & Research
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JOB TITLE: C-BRAIN Data Engineer (Remote) - Neurology
The C-BRAIN Data Engineer joins the C-BRAIN team to design, build, and maintain the data infrastructure powering AI biomedical research tools. This role involves developing scalable data ingestion pipelines, ETL/ELT workflows, and cloud infrastructure to harmonize multi-modal neurodegeneration datasets, including omics, neuroimaging, and clinical records. You will manage storage, compute resources, and access controls while ensuring data quality and lineage for agentic AI tools like InsightEngine. Key technologies include Python, SQL, Apache Spark, dbt, Airflow, and Microsoft Azure. The position requires deep domain knowledge of neurodegeneration or Alzheimer’s disease research data to reconcile diverse datasets from sources like NACC and ADNI into unified analytical frameworks. You will ensure all data handling complies with DUA terms and PHI de-identification requirements within a research environment.
What does a Data Engineer earn?
Median $159000 from 203 postings across 58 companies.
Design, build, and maintain scalable data ingestion pipelines to integrate multi-modal neurodegeneration datasets into the C-BRAIN infrastructure.
Develop and maintain ETL/ELT workflows using tools like Apache Spark, dbt, and Airflow to ensure robust and auditable data processing.
Harmonize diverse data types including omics, neuroimaging, and clinical records into unified analytical frameworks for AI tool consumption.
Manage and optimize cloud infrastructure, including storage accounts, compute resources, data lakes, and access controls.
Implement data quality validation checks and maintain comprehensive data lineage documentation to ensure reproducibility and accuracy.
Enforce data governance by managing access permissions, de-identification workflows, and compliance with Data Use Agreements (DUA).
Maintain a comprehensive data catalog and technical documentation for all pipelines, infrastructure configurations, and metadata records.
Provide technical specifications for data delivery methods and monitor the receipt and completeness of contributed datasets.
What we're looking for
Bachelor's degree in Computer Science, Data Science, Bioinformatics, Engineering, or a closely related field.
Master's degree, PhD, or terminal degree (preferred).
Three years of hands-on data engineering experience, including design and development of data pipelines and ETL/ELT workflows in a production or research environment.
Demonstrated proficiency in Python and SQL.
Demonstrated software engineering background with production-grade Python, version control (Git), code review practices, and automated testing.
Experience with cloud data platforms, specifically Microsoft Azure (preferred), AWS, or GCP.
Experience working with at least two biomedical data modalities, such as omics, neuroimaging, digital pathology, or longitudinal clinical/EHR data.
Demonstrated experience working with neurodegeneration or Alzheimer’s disease research datasets, including familiarity with NACC, ADNI, and/or AD/ADRD repositories.