Data Engineer, Neurology

What you'll do

• 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, or Airflow while ensuring code is version-controlled and documented.
• Harmonize diverse data types including omics, neuroimaging, and clinical records into unified, analysis-ready frameworks for AI tool consumption.
• Manage cloud infrastructure operations, including storage accounts, compute resources, access controls, and cost optimization on platforms like Azure.
• Implement data quality validation checks and maintain comprehensive lineage documentation to ensure reproducibility of all transformations.
• Ensure all data handling complies with Data Use Agreements (DUA) and PHI de-identification requirements for biomedical research.
• Maintain a comprehensive data catalog including metadata records, data dictionaries, and access procedures for internal and external stakeholders.
• Provide technical specifications for data delivery methods and coordinate the validation of incoming datasets against contract requirements.

What we're looking for

• Bachelor's degree in Computer Science, Data Science, Bioinformatics, Engineering, or a related field.
• Three years of hands-on data engineering experience including production-grade Python and SQL.
• Experience with cloud platforms such as Microsoft Azure (preferred), AWS, or GCP.
• Demonstrated software engineering skills including Git version control, code reviews, and automated testing.
• Experience working with at least two biomedical modalities like omics, neuroimaging, digital pathology, or clinical records.
• Proven experience with neurodegeneration or Alzheimer’s disease research datasets and the associated data landscape.
• Master's degree or PhD in a related field (preferred).
• Experience with tools such as Apache Spark, dbt, Airflow, or Azure Data Factory (preferred).