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Data Engineer

Data Engineer

iHireFelton, CA, US
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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.

About The Position

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.

You will find this position a good fit if you are passionate about transforming raw healthcare data into valuable insights, believe in the critical role of robust data curation in advancing machine learning in healthcare, and thrive in environments where you can work independently on complex data challenges while collaborating with multidisciplinary teams.

Responsibilities

  • 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.
  • 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.

Key Responsibilities

  • Data Pipeline Engineering : Design, implement, and maintain robust pipelines for the programmatic cleaning, transformation, and curation of healthcare data.
  • 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.
  • Healthcare Data Expertise : Work extensively with patient-level health data, ensuring that data handling practices adhere to industry regulations and ethical standards.
  • Requirements

  • 3+ years of experience in software development and data engineering with a strong focus on data cleaning, transformation, and creation.
  • Proficiency in Python and experience with data processing libraries (e.g., Pandas, Polars, NumPy).
  • Hands-on experience in building and maintaining automated data pipelines for large-scale data processing.
  • Familiarity with machine learning frameworks (e.g., PyTorch, JAX, scikit-learn) as applied to data quality and augmentation tasks.
  • Expertise in working with healthcare data, including familiarity with the OMOP Common Data Model (OMOP CDM).
  • Preferred Qualifications

  • Experience with cloud platforms (e.g., GCP, AWS, or Azure) and distributed computing frameworks.
  • Proficiency with version control systems (e.g., Git) and containerization tools (e.g., Docker).
  • Familiarity with healthcare data standards and regulatory requirements.
  • The expected pay range for this position is $157,945 to $177,385 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position.

    Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

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    Data Engineer • Felton, CA, US

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