ML Data Engineer – Healthcare Data Curation & Cleaning

ML Data Engineer – Healthcare Data Curation & Cleaning (1 Year Fixed Term)

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ML Data Engineer – Healthcare Data Curation & Cleaning (1 Year Fixed Term)🔍School of Medicine, Stanford, California, United States📁Information Analytics📅Jun 03, 2025 Post Date📅106579 Requisition #StAnford University is seeking a Big Data Architect 1 for a 1‑year fixed term (possibility of renewal) to design and develop applications, test and build automation tools, and support the development of Big Data architecture and analytical solutions.

The Department of Biomedical Data Science merges the disciplines of biomedical informatics, biostatistics, computer science and advances in AI. The intersection of these disciplines is applied to precision health, leveraging data across the entire medical spectrum, including molecular, tissue, medical imaging, EHR, biosensory and population data.

We are seeking an experienced ML Data Engineer to drive the programmatic curation, cleaning, and generation of healthcare data. In this role, you will focus exclusively on developing and maintaining automated, ML‑accelerated pipelines that ensure high‑quality data ready for machine learning applications. Your work will be pivotal in shaping the integrity of our data and supporting downstream predictive models in a complex healthcare environment.

• You are passionate about transforming raw healthcare data into valuable insights.
• You believe in the critical role of robust data curation in advancing machine learning in healthcare.
• You thrive in environments where you can work independently on complex data challenges while collaborating with multidisciplinary teams.
• You are excited to work with patient‑level data and embrace challenges related to data diversity and complexity.

• Design Big Data systems that are scalable, optimized, and fault‑tolerant.
• Work closely with scientific staff, IT professionals, and project managers to understand their data requirements for existing and future projects involving Big Data.
• Develop, test, implement, and maintain database management applications. Optimize and tune the system, perform software review and maintenance to ensure that data design elements are reusable, repeatable, and robust.
• Contribute to the development of guidelines, standards, and processes to ensure data quality, integrity and security of systems and data appropriate to risk.
• Participate in and/or contribute to setting strategy and standards through data architecture and implementation, leveraging Big Data, analytics tools and technologies.
• Work with IT and data owners to understand the types of data collected in various databases and data warehouses.
• Research and suggest new toolsets/methods to improve data ingestion, storage, and data access.

• Data Pipeline Engineering:
  • Design, implement, and maintain robust pipelines for the programmatic cleaning, transformation, and curation of healthcare data.
  • Develop automated processes to curate and validate data, ensuring accuracy and compliance with healthcare standards (e.g., OMOP CDM, FHIR).
• ML Data Engineering:
  • Leverage core machine learning techniques to generate datasets, clean existing health records, join heterogeneous data sources, and enhance data quality for model training.
  • Implement innovative solutions to detect and correct data inconsistencies and anomalies in large‑scale healthcare datasets.
• Healthcare Data Expertise:
  • Work extensively with patient‑level health data, ensuring that data handling practices adhere to industry regulations and ethical standards.
  • Utilize the OMOP Common Data Model (OMOP CDM) to standardize and harmonize disparate healthcare data sources, enhancing interoperability and scalability.
• Collaboration & Continuous Improvement:
  • Collaborate closely with data scientists, clinical informaticians, and engineers to align data engineering practices with analytical and clinical requirements.
  • Continuously monitor, troubleshoot, and optimize data workflows to support dynamic…