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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 processes can be audited and transferred. Documentation and Reporting Maintains comprehensive technical documentation for all pipelines, infrastructure configurations, and data architecture decisions in the C-BRAIN documentation repository. Develops and maintains a C-BRAIN data catalog: documents available datasets, data dictionaries, lineage, and access procedures. Contributes technical content to C-BRAIN progress reports, Steering Committee materials, and grants reporting as requested by the CTO or Senior Technical Product Manager. Working Conditions: Office environment (remote or hybrid per current Washington University policies). Occasional on-site presence required for team meetings and consortium events. Job Location/Working Conditions Normal office environment Occasional on-site presence required for in-person meetings, team meetings, and consortium events. Physical Effort Typically working at desk or table Repetitive wrist, hand or finger movement Ability to move to on and off-campus locations Primarily sedentary with standard computer use. Equipment Office equipment The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time. Education: Required Qualifications Bachelor's degree Certifications /Professional Licenses : No specific certification/professional license is required for this position. Work Experience: Relevant Experience (3 Years) Skills: Not Applicable Driver's License: A driver's license is not required for this position. Required Qualifications: More About This Job 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 develop
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
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When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.