Bioinformatics Engineer II (Hybrid Opportunity)

Join to apply for the Bioinformatics Engineer II (Hybrid Opportunity) role at Stanford University School of Medicine Join to apply for the Bioinformatics Engineer II (Hybrid Opportunity) role at Stanford University School of Medicine Get AI-powered advice on this job and more exclusive features. The Department of Medicine, Division of Cardiovascular Medicine at Stanford University is seeking a talented Bioinformatics Engineer to join the Bioinformatics Core (BIC) of the Molecular Transducers of Physical Activity Consortium (MoTrPAC). As part of this groundbreaking national research consortium, you will help unravel the molecular mechanisms underlying the benefits of physical activity. Under the supervision of co-PIs Dr. Euan Ashley and Dr. Matthew Wheeler, you will play a crucial role in shaping the future of personalized exercise science and public health. Dr. Euan Ashley's research interests focus on the application of genomics and other omics data to improve clinical care, with an emphasis on cardiovascular disease and personalized medicine. Dr. Matthew Wheeler's research centers on the integration of large-scale molecular and clinical data to understand the genetic basis of cardiovascular diseases and to develop novel therapeutic strategies. As a key member of the MoTrPAC team, your expertise in data engineering and bioinformatics software development will form the bedrock of our research infrastructure. You will be responsible for architecting and implementing the scalable data pipelines, standardized data models (like OMOP), and robust bioinformatic applications that transform raw, complex omics data into clean, analysis-ready datasets for the entire consortium, under the supervision of our lead informatician. Your work is critical for our team to apply advanced statistical and machine learning methods, directly contributing to our understanding of complex biological systems and the development of personalized medicine. This innovative project integrates large volumes of clinical and densely time-sampled molecular data, pushing the boundaries of biomedical data analytics. Our portal ( will push the boundaries of biomedical data analytics to provide insight into the basic and translational science of exercise. Working alongside our multidisciplinary team, you will be at the forefront of understanding how physical activity preserves and improves health, ultimately making a lasting impact on human well-being. Responsibilities As a Bioinformatics Engineer II, you will take ownership of critical data engineering and software development tasks that form the backbone of the MoTrPAC project. Your primary responsibilities will include: Data Engineering & ETL Pipelines: Engineer, maintain, and enhance robust ETL (Extract, Transform, Load) pipelines to process, clean, and map diverse data types. This includes managing pipelines for human and animal phenotype data to generate clean, summary datasets for public and consortium release. Data Standardization: Lead the transformation of MoTrPAC clinical data into standardized formats like the OMOP Common Data Model (CDM), enabling large-scale, federated data analysis and integration. Scientific Visualization Workflows: Develop and automate workflows to generate scientific visualizations (e.g., ATAC-seq tracks for IGV) that compare accessibility differences between study cohorts and support biological interpretation by our research team. Bioinformatics Tooling & Software Development: Refactor, extend, and package bioinformatic tools (e.g., Python packages) to streamline complex processes, such as the generation of mwTab files for metabolomics data submission. Data Management and Tracking: Design and implement data tracking systems to provide clear visibility into the status of raw and processed assays across cloud storage environments, improving data accessibility and usability for all consortium members. Collaboration and Communication: Collaborate with a multidisciplinary team of scientists and engineers to interpret large-scale multi-omics data and prepare reports and presentations to communicate findings effectively. Duties Include Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness. Determine additional data collection and reporting requirements. Design and customize reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data. Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others. Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation. Serve as a resource for non-routine inquiries such as requests for statistics or surveys. Test prototype software and participate in approval and release process for new software. Provide documentation based on audit and reporting criteria to investigators and research staff. Why Join Us? Work on a highly exciting and innovative multi-omics project with the potential to revolutionize our understanding of physical activity and health. Be part of a world-class research team at Stanford University, led by Dr. Euan Ashley, a pioneer in personalized medicine. Contribute to groundbreaking research with a significant impact on public health and the prevention of diseases. Enjoy a collaborative and stimulating work environment at one of the top universities in the world. If you are a passionate and dedicated professional with the required qualifications and a strong interest in advancing scientific research, we encourage you to apply for this exciting opportunity. Join us in unraveling the mysteries of physical activity and making a lasting impact on human health. A complete application will include a cover letter. This is a hybrid eligible position. Desired Qualifications Expertise in Clinical Data Standardization: Direct experience with the OMOP Common Data Model (CDM), including developing ETL processes, mapping clinical data, and understanding the model's structure and purpose. Advanced Python for Data Engineering: Deep proficiency in Python, particularly with libraries central to data manipulation (Pandas, Polars), database interaction (SQLAlchemy), and scientific computing (NumPy). Bioinformatics Software Development Experience: A proven track record of refactoring, extending, and packaging bioinformatics tools for distribution (e.g., using setuptools, PyPI), demonstrating an understanding of software development best practices like version control, testing, and documentation. Specialized Cloud and Database Skills: Hands-on experience with cloud-based data warehousing and database solutions, particularly Google Cloud Platform (GCP) services like BigQuery and Cloud Storage. Specific Omics Data Experience: Familiarity with the data structures, QC metrics, and visualization strategies for epigenomics (ATAC-seq) and metabolomics data. Experience creating data tracks for genome browsers (e.g., IGV) is a strong plus. Data Governance and Tracking Acumen: A demonstrated interest or experience in designing systems for data tracking, provenance, and improving data visibility and accessibility within a large research consortium. Robust Experience with Workflow Managers: Extensive experience building, debugging, and deploying complex scientific workflows using languages like Nextflow or WDL in a cloud or HPC environment. Proven Expertise in Data Engineering: Demonstrated experience engineering and maintaining data pipelines, including ETL processes, data cleaning, and data validation. Experience with data modeling and standards (e.g., OMOP CDM) is highly desirable. Strong Programming Skills: Proficiency in Python and Linux bash scripting is essential. Pipeline and Cloud Proficiency: Hands-on experience with workflow management languages (e.g., Nextflow, WDL), container systems (Docker), and cloud computing environments (GCP, Azure). Experience with databases (SQL, BigQuery) is a strong plus. Bioinformatics Acumen: Strong understanding of omics data (e.g., ATAC-seq, metabolomics) and experience with standard bioinformatics tools (e.g., samtools, bcftools). Collaborative Mindset: A track record of success in team-based software development projects, with strong communication skills and the ability to work both independently and in a highly collaborative environment. Education & Experience (required) Bachelor's degree in bioinformatics, computer science, data science, statistics, or a related field and three years of relevant experience or combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering. Knowledge, Skills And Abilities (required) Substantial experience with MS Office and analytical programs. Excellent writing and analytical skills. Ability to prioritize workload. Certifications & Licenses None

PHYSICAL REQUIREMENTS*:

Sitting in place at computer for long periods of time with extensive keyboarding/dexterity. Occasionally use a telephone. Rarely writing by hand. Working Conditions Some work may be performed in a laboratory or field setting. Working Standards Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations. Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned. Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University’s Administrative Guide, The expected pay range for this position is $108,002 to $128,138 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. Why Stanford is for You Benefits Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our culture and unique perks empower you with: Freedom to grow. We offer career development programs, tuition reimbursement, or audit a course. Join a TedTalk, film screening, or listen to a renowned author or global leader speak. A caring culture. We provide superb retirement plans, generous time-off, and family care resources. A healthier you. Climb our rock wall or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits. Discovery and fun. Stroll through historic sculptures, trails, and museums. Enviable resources. Enjoy free commuter programs, ridesharing incentives, discounts and more. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form. 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. The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Research, Analyst, and Information Technology Industries Higher Education Referrals increase your chances of interviewing at Stanford University School of Medicine by 2x Sign in to set job alerts for “Bioinformatics Engineer” roles. San Mateo, CA $121,667.00-$187,833.00 1 month ago Stanford, CA $108,002.00-$128,138.00 3 days ago AI/ML Engineer (Multiple roles and seniority levels) Bioinformatics Software Engineer, AI Applications - Keplogic Redwood City, CA $85,000.00-$145,000.00 2 weeks ago Palo Alto, CA $180,000.00-$440,000.00 2 weeks ago Mountain View, CA $124,500.00-$186,500.00 4 days ago Sunnyvale, CA $112,000.00-$185,000.00 1 day ago Bioinformatics Engineer, Biomedical Knowledge Base Redwood City, CA $130,000.00-$170,000.00 4 weeks ago Full Stack Software Engineer (L4), Product Localization Engineering Research Engineer (LLMs and Generative Models) Redwood City, CA $160,000.00-$210,000.00 4 days ago AI Engineer & Researcher - Post-training South San Francisco, CA $39.60-$78.95 5 days ago Redwood City, CA $172,000.00-$240,000.00 3 days ago San Jose, CA $150,000.00-$160,000.00 1 week ago Machine Learning Engineer (I, II, or Sr.) We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr Stanford University School of Medicine