Job DescriptionJob Description
Join our team at the intersection of engineering and science. We're building a genomic diagnostics platform that transforms raw sequencing data into clinically actionable insights—and we need a talented engineer to help us scale it.
You'll own critical pieces of our backend infrastructure and analytical pipelines, working alongside scientists and bioinformaticians to solve complex problems in a regulated clinical environment. If you thrive on building systems that process massive datasets with precision and reproducibility, this is your opportunity.
What You'll Do
Architect and maintain production-grade analytical pipelines for genomic data—from ingestion through transformation, validation, and distributed processingBuild and optimize cloud-based backend systems (GCP preferred) designed for high-volume sequential data processingWork with workflow orchestration tools (WDL, Cromwell, Nextflow, Airflow, or similar) to automate and scale scientific workflowsEnsure pipeline reproducibility through containerization (Docker) and rigorous version control practicesMaintain strict PHI handling, data privacy, and compliance standards within our clinical environmentPartner with scientists and bioinformaticians to translate analytical requirements into scalable, production-ready solutions
What You Bring
Strong foundation in computational sciences, bioinformatics, or a related quantitative fieldProven track record building and deploying data pipelines in production scientific environmentsHands-on experience with large-scale genomic or scientific datasetsProficiency in Python, Java, or similar languagesWorking knowledge of cloud infrastructure (GCP ideal) and distributed processing frameworksFamiliarity with containerization, CI/CD, and reproducible research practicesUnderstanding of data privacy requirements and PHI handling in clinical/research settingsAbility to communicate effectively across technical and scientific teams
Nice to Have
Background in biotech, diagnostics, or genomicsExperience with HPC-style workflows and batch processing at scaleExposure to regulated clinical environments (CLIA, CAP, HIPAA)
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