Bioinformatics Engineer

OverviewThe Bioinformatics Engineer will support the GREGoR Stanford Site (GSS) pipeline and data analysis team, focusing on development of pipelines and tools for comprehensive analysis of large multi-omics datasets (genomics, transcriptomics, metabolomics) and establishing cloud infrastructure for storage and computation.Location: Stanford University, On Site. This role requires the ability to understand biological experiments, strong experience with large-scale biological data analysis, programming proficiency, and experience in high-performance computing or cloud environments.Duties IncludeDevelopment of pipelines and tools for the comprehensive analysis of large amounts of multi-omics data generated by the GSS.Establish and maintain the cloud infrastructure for GSS on AnVIL and Google Cloud Platform (GCP).Interact with GREGoR team members and external tool developers to implement new tools, algorithms, and updates.Develop intuitive reports for molecular pipelines to track progress and quality metrics.Monitor and report problems with pipeline analysis and underlying data.Extract relevant data from diverse sources, including RESTful APIs, databases, and medical records.Serve as a resource for bioinformatics inquiries from the clinical team to access data or results from local clusters/cloud/external providers.Collaborate with stakeholders across the consortium to model metadata schemas and understand data structures.Mentor Junior Analysts regarding primary analysis.Document and report as needed to fulfill grant and regulatory obligations.Due to the nature of the work, this position is fully onsite.Other duties may also be assigned.QualificationsEducation & Experience (Required): Bachelor’s degree and three years of relevant experience or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics, or engineering.Graduate degree (Ph.D. or M.S.) in bio/medical informatics, engineering, computer science, and statistics is preferred.Domain expertise in analysis and running pipelines for at least one of: genomics, transcriptomics, metabolomics, ATAC-seq, proteomics.Proficiency in Python and/or R and Linux bash scripting.Experience with pipeline languages like WDL, Snakemake, or Nextflow.Proven track record of data and infrastructure management in an HPC cluster or cloud (GCP/AWS).Experience with container systems (VMs, Docker).Experience with code management (GitHub).Strong communication skills and ability to work independently; collaborative NIH consortium experience is a plus.Willingness to learn and adapt to new tools and methods.Knowledge, Skills, and Abilities (Required)Substantial experience with MS Office and analytical programs.Excellent writing and analytical skills; ability to prioritize workload.Physical RequirementsSitting for long periods at a computer with extensive keyboarding.Occasionally using a telephone; rarely writing by hand.Reasonable accommodation available for disability per university pensation & BenefitsThe expected pay range is $108,002 to $128,138 per annum. Stanford provides a comprehensive rewards package; details are discussed during the hiring process. See the Cardinal at Work site for benefits information.About StanfordStanford University 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. #J-18808-Ljbffr

Created: 2025-09-17