C-BRAIN Data Engineer (Remote) - Neurology

About this role

Location Remote, US

 Scheduled Hours 40

Position Summary The C-BRAIN Data Engineer is a key technical member of the C-BRAIN team responsible for designing, building, and maintaining the data infrastructure that powers C-BRAIN's AI tools. Reporting to the C-BRAIN Chief Technology Officer (CTO), this role is responsible for all aspects of data ingestion, pipeline development, data harmonization, and cloud infrastructure management — ensuring that high-quality, analysis-ready data is available to C-BRAIN's AI tools and research teams. C-BRAIN is building an AI Biomedical Research Scientist platform that integrates diverse multi-institutional datasets (including NACC, ADNI, and consortium member data contributions). The Data Engineer will be central to building the technical infrastructure that makes this platform possible, working in close partnership with the CTO, the Senior Technical Product Manager, and external data science collaborators. This is not a standard data pipeline position. The Data Engineer is building the technical backbone of an AI biomedical research platform — infrastructure that must ingest and harmonize multi-modal neurodegeneration datasets at consortium scale and serve as the data foundation for agentic AI tools including InsightEngine and OpenScientist. The ideal candidate brings software engineering discipline, strong cloud platform experience, and demonstrated knowledge of neurodegeneration or biomedical research data. Domain knowledge is a prerequisite, not a nice-to-have; C-BRAIN-specific context will be provided, but neurodegeneration data experience and software engineering fundamentals will not.

Job Description

Primary Duties & Responsibilities:

Data Pipeline Development and Maintenance • Designs, builds, tests, and maintains scalable data ingestion pipelines to ingest consortium member datasets from diverse sources and formats into the C-BRAIN data infrastructure. • Develops and maintains ETL/ELT workflows using tools such as Apache Spark, dbt, Airflow, or equivalent; ensure pipelines are robust, well-documented, and auditable. • Implements automated pipeline monitoring and alerting; troubleshoot and resolves pipeline failures in a timely manner. • Works collaboratively with the CTO and data science teams to understand data requirements for AI tool development and translates those requirements into technical pipeline specifications. • Maintains version control for all pipeline code and infrastructure configurations; follows software engineering best practices including code review and documentation. • Integrates and processes multi-modal data including omics (genomics, transcriptomics, proteomics), neuroimaging (PET, MRI), longitudinal clinical records, and digital pathology — reconciling differences in data type, format, spatial resolution, and dimensionality into unified analytical frameworks. • Identifies where cross-modal integration produces genuine signal versus where it introduces noise or artifact; establishes ground truth benchmarks for downstream AI use.

Data Infrastructure and Cloud Operations • Manages and optimizes the C-BRAIN data infrastructure: storage accounts, computes resources, data lakes, and access controls. • Implements and maintains data access controls and permissions aligned with DUA requirements and WashU data governance policies. • Collaborates with the CTO on cloud architecture decisions; contributes to infrastructure planning for Phase 2 scale-up including foundation model compute requirements. • Monitors infrastructure costs, resource utilization, and performance; identifies and implements optimization opportunities. • Supports the deployment of C-BRAIN AI tools on cloud-based platforms; coordinates with technical teams on infrastructure requirements. • Ensures all data handling complies with DUA terms and applicable PHI de-identification requirements; implements, documents, and maintains de-identification workflows for each incoming dataset. • Uploads curated datasets to ADDI/AD Workbench and other designated repositories (NIAGADS, GP2, or equivalent) as directed; manages access controls within the platform to ensure data is accessible only by authorized users and tools.

Data Harmonization and Quality • Develops and implements data harmonization procedures to integrate datasets from multiple sources (NACC, ADNI, consortium member contributions) into a unified, analysis-ready format. • Implements data quality validation checks at ingestion and transformation stages; documents data quality issues and coordinates resolution with data providers. • Maintains comprehensive data lineage documentation: tracks data from source to consumption, documents all transformations, and ensures reproducibility. • Collaborates with research scientists and the AD, Scientific to understand scientific data requirements and ensures data products meet research use case specifications. • Aligns incoming datasets to established biomedical data standards including AD Workbench, ADDI, NIAGADS, and GP2; builds and maintains data dictionaries and metadata records for each ingested dataset.

DUA Technical Support and Data Delivery • Provides technical input on Data Use Agreements: defines technical specifications for data format, delivery method, transfer protocols, and storage requirements in coordination with the Senior Technical Product Manager. • Confirms receipt of contributed datasets, validates format and completeness against DUA specifications, and logs acceptance in the DUA register. • Flags data quality, completeness, or format issues to the Senior Technical Product Manager and CTO for follow-up with data contributors. • Supports technical aspects of the data delivery monitoring process: tracks expected deliveries, confirms receipt, and maintains data delivery logs. • Supports beta testing of data ingestion tools and provides structured feedback to development partners; maintains clear, reproducible documentation so pipeline processe

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