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Data Engineer - Healthcare Data Management
$157,945 - 177,385
Stanford University
Knight Way, Stanford
$157,945 - 177,385
Requirements
Must:
- A Bachelor’s degree in a scientific or analytical field and five years of relevant experience, or a combination of education and relevant experience.
- At least 3 years of experience in software development and data engineering, with a strong emphasis on data cleaning, transformation, and creation.
- Proficiency in Python and experience with data processing libraries (e.g., Pandas, Polars, NumPy).
- Hands-on experience in designing 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 enhancement tasks.
- Expertise in dealing with healthcare data, including knowledge of the OMOP Common Data Model (OMOP CDM).
- Strong experience in a Linux environment and comfort with UNIX command-line tools.
- Proven ability to collaborate in multidisciplinary teams and communicate technical concepts effectively.
- Preferred: 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.
Responsibilities
- Design scalable, optimized, and fault-tolerant Big Data systems.
- Collaborate with scientific staff, IT professionals, and project managers to assess their data needs for current and upcoming projects related to Big Data.
- Develop, test, implement, and maintain database management applications, optimizing and tuning systems to ensure reusable, repeatable, and robust data design elements.
- Contribute to the formulation of guidelines, standards, and processes that ensure data quality, integrity, and system security appropriate to risk.
- Engage in establishing strategies and standards through data architecture and implementation utilizing Big Data, analytics tools, and technologies.
- Work with IT and data owners to comprehend the data collected across various databases and data warehouses.
- Research and propose new toolsets/methods to enhance data ingestion, storage, and accessibility.
- Design, implement, and maintain robust data pipelines for the programmatic cleaning, transformation, and curation of healthcare data.
- Leverage machine learning techniques to create datasets, clean existing health records, join diverse data sources, and improve data quality for model training.
- Ensure that patient-level health data is handled in accordance with industry regulations and ethical standards, utilizing the OMOP CDM to standardize and harmonize disparate healthcare data sources.
- Collaborate closely with data scientists, clinical informaticians, and engineers to synchronize data engineering practices with analytical and clinical needs.
- Continuously monitor, troubleshoot, and optimize data workflows to support evolving research and operational requirements.
Description
We are offering a one-year fixed-term position as a Big Data Architect 1, with a possibility of renewal, at Stanford University. This role is integral to the design and development of applications, testing, building automation tools, and supporting the establishment of Big Data architecture and analytical solutions within our Department of Biomedical Data Science. Our department integrates biomedical informatics, biostatistics, computer science, and advancements in AI, applying these disciplines to precision health across the medical spectrum, including molecular, tissue, medical imaging, EHR, biosensory, and population data. The expected salary range for this position is between $157,945 and $177,385 annually, reflecting our good faith estimate of what we anticipate paying. Salary determination will be influenced by several factors, including scope and responsibilities, qualifications, departmental budget, internal equity, geographic location, and external market compensation. At Stanford University, base pay is just one aspect of our comprehensive reward offerings. Additional details on benefits and rewards can be found on the Cardinal at Work website. We are committed to providing reasonable accommodations for applicants and employees with disabilities. Our hiring process is inclusive, and we welcome applications from individuals who will add diverse perspectives to our research mission, irrespective of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other legally protected characteristics.
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You can find Data Engineer salaries in the United States here.
How many Data Engineer jobs are in the United States?
Currently, there are 895 Data openings. Check also: Spark jobs, Snowflake jobs, Kafka jobs, Hadoop jobs - all with salary brackets.
Is the US a good place for Data Engineers?
The US is one of the best countries to work as a Data Engineer. It has a vibrant startup community, growing tech hubs and, most important: lots of interesting jobs for people who work in tech.
Which companies are hiring for Data Engineer jobs in the United States?
Sperasoft, Bain Magique, Archon Systems Inc, Journey Freight International inc, Puter Technologies Inc., Ontario One Call, HAPLY Robotics Inc. among others, are currently hiring for Data roles in the United States.
The company with most openings is Leidos as they are hiring for 88 different Data Engineer jobs in the United States. They are probably quite committed to find good Data Engineers.
The company with most openings is Leidos as they are hiring for 88 different Data Engineer jobs in the United States. They are probably quite committed to find good Data Engineers.