Data Engineer – Neurology

WashU IT

Data Engineer building cloud pipelines and harmonized biomedical datasets for Washington University’s C-BRAIN AI research platform. Supporting neurodegeneration research, data governance, and AI tool deployment.

Posted 8/19/2026full-time🇺🇸 United StatesMid-LevelSenior💰 $75,200 - $128,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data ingestion pipelines, with proficiency in ETL/ELT workflows using tools like Apache Spark and Airflow. Strong background in managing complex biomedical datasets and ensuring data quality and compliance with governance policies.

Highest-signal resume keywords

Data Pipeline DevelopmentETL/ELT WorkflowsPython ProgrammingCloud Data PlatformsBiomedical Data Integration

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Applicant Tracking System Keywords

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Hard Skills

Data Ingestion PipelinesETL/ELT WorkflowsApache SparkAirflowPythonSQLData Quality ValidationData LineageVersion Control (Git)Automated Testing

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

Microsoft AzureAWSGCPDbtAzure Data FactoryADDISynapseTerraC-BRAIN AI ToolsData Catalogs

Industry Keywords

BioinformaticsNeuroimagingLongitudinal Clinical RecordsDigital PathologyData GovernanceData Use AgreementsNeurodegeneration ResearchAlzheimer’s DiseaseNACCADNI

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCloudETLGoogle Cloud PlatformNeo4jPythonSparkSQL

About the role

Key responsibilities & impact

Design, build, test, and maintain scalable data ingestion pipelines for consortium datasets
Develop and maintain ETL/ELT workflows using Apache Spark, dbt, Airflow, or equivalent tools
Implement pipeline monitoring and alerting; troubleshoot and resolve failures
Translate AI tool data requirements into technical pipeline specifications
Maintain version control, code reviews, documentation, and software engineering best practices
Integrate and process omics, neuroimaging, longitudinal clinical records, and digital pathology data
Establish cross-modal integration signal-versus-noise assessments and ground-truth benchmarks
Manage and optimize storage accounts, compute resources, data lakes, and access controls
Implement permissions aligned with Data Use Agreements and WashU governance policies
Contribute to cloud architecture and Phase 2 infrastructure planning
Monitor infrastructure costs, utilization, and performance and implement optimizations
Support deployment of C-BRAIN AI tools on cloud platforms
Implement and maintain PHI de-identification workflows
Upload curated datasets to ADDI/AD Workbench, NIAGADS, GP2, or equivalent repositories
Develop data harmonization procedures and quality validation checks
Maintain data lineage, data dictionaries, metadata records, and the C-BRAIN data catalog
Coordinate data quality issue resolution with data providers and research scientists
Provide technical input on Data Use Agreements and data delivery specifications
Confirm, validate, and log contributed dataset deliveries
Support beta testing of data ingestion tools and document reproducible processes
Prepare technical content for progress reports, Steering Committee materials, and grants reporting
Report to the C-BRAIN Chief Technology Officer and collaborate with the Senior Technical Product Manager, research scientists, and external data science collaborators

Requirements

What you’ll need

Bachelor's degree in Computer Science, Data Science, Bioinformatics, Engineering, or a closely related field
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
Experience with cloud data platforms; Microsoft Azure preferred, AWS or GCP acceptable
Familiarity with cloud storage, compute, and access control management
Experience with complex, multi-source datasets requiring integration, harmonization, and quality validation
Production-grade Python experience with version control (Git), code review practices, and automated testing
Experience with at least two biomedical data modalities: omics, neuroimaging, digital pathology, or longitudinal clinical/EHR data
Demonstrated experience working with neurodegeneration or Alzheimer’s disease research datasets
Familiarity with the neurodegeneration data landscape, including NACC, ADNI, and/or AD/ADRD repositories
Sufficient biological context to communicate meaningfully with research scientists
No specific certification/professional license is required
Driver’s license is not required
Preferred: experience with biomedical, clinical, or research datasets in an academic medical center, research university, or life sciences organization
Preferred: experience with ADDI, Synapse, Terra, or NACC/ADNI data platforms
Preferred: experience with Apache Spark, dbt, Airflow, Azure Data Factory, or equivalent ETL/ELT frameworks
Preferred: familiarity with data governance frameworks, data use agreements, or federated data architectures
Preferred: experience supporting AI/ML or data science teams
Preferred: experience with NAIRR or other research cloud computing platforms
Preferred: experience with data catalogs, data lineage platforms, or metadata management
Preferred: familiarity with de-identification standards and privacy-preserving data techniques
Preferred: Master’s or PhD in Computer Science, Data Science, Bioinformatics, Biomedical Informatics, or a related field
Preferred: familiarity with agentic AI frameworks, RAG, or LLM-based co-scientist systems
Preferred: biomedical NLP experience, including named entity recognition, natural language inference, or knowledge graph construction
Preferred: knowledge of graph data structures and platforms such as Neo4j or Amazon Neptune
Preferred: track record of cross-disciplinary collaboration

Benefits

Comp & perks

Up to 22 days of vacation
10 recognized holidays
Sick time
Competitive health insurance packages with priority appointments and lower copays/coinsurance
Free Metro transit U-Pass for eligible employees
Defined contribution 403(b) Retirement Savings Plan, with university contributions starting at 7%
Wellness challenges
Annual health screenings
Mental health resources
Mindfulness programs and courses
Employee assistance program (EAP)
Financial resources
Access to dietitians
4 weeks of caregiver leave to bond with your new child
Family care resources for continued childcare needs
Adult care support
Tuition coverage for employees and families, including dependent undergraduate-level college tuition up to 100% at WashU and 40% elsewhere after seven years
Remote or hybrid work per current Washington University policies
Reasonable accommodations for employees with disabilities