Job Description
Job Description
Job DescriptionRole Summary:
We are seeking a highly skilled engineer to develop and maintain our genomic diagnostics platform, transforming raw genomic and scientific datasets into clinically actionable insights. The role involves backend development, workflow orchestration, and cloud infrastructure, with a strong emphasis on scientific computing and analytical pipelines. The ideal candidate will collaborate closely with scientists, bioinformaticians, and cross-functional teams to build scalable, production-ready pipelines in a regulated, clinical environment.
Responsibilities:
- Develop and maintain a genomic diagnostics platform and associated backend systems.
- Lead or own pipeline and workflow architecture in production environments.
- Design, implement, and optimize analytical pipelines for large-scale scientific or genomic datasets, including ingestion, transformation, validation, and distributed processing.
- Work with workflow orchestration tools such as WDL, Cromwell, Nextflow, Airflow, or equivalents.
- Build cloud-based backend systems, ideally on GCP, capable of handling large volumes of sequential data processing.
- Ensure containerization and reproducibility of pipelines using Docker or other container technologies.
- Maintain strong PHI handling, data privacy, and compliance practices in scientific or clinical environments.
- Collaborate with cross-functional teams to translate complex analytical requirements into scalable engineering solutions.
- Focus on scientific computing, HPC-style workflows, and large-scale data ingestion systems.
Required Qualifications:
- Strong academic foundation in computational or life sciences.
- Significant experience with backend development in data-intensive scientific environments.
- Expertise with large-scale genomic or scientific datasets.
- Proven ability to build, deploy, and maintain analytical pipelines in production environments.
- Hands-on experience with workflow orchestration and cloud infrastructure.
- Familiarity with containerization and reproducibility technologies.
- Deep understanding of data privacy, PHI, and compliance requirements in clinical or research settings.
- Excellent collaboration and communication skills to work effectively with scientists, bioinformaticians, and engineers.
Preferred Qualifications:
- Experience in biotech, diagnostics, genomics, or other data-intensive scientific domains.
- Familiarity with high-performance computing (HPC) workflows.
- Experience supporting large-scale sequential or batch data processing in cloud environments.
- Knowledge of modern software engineering practices, testing, CI/CD, and reproducible research pipelines.
Skills & Competencies:
- Analytical and problem-solving mindset with a focus on scalable engineering solutions.
- Ability to translate complex scientific requirements into practical computational workflows.
- Strong programming and software development skills in Python, Java, or similar languages.
- Hands-on experience with cloud platforms, ideally GCP, and distributed data processing frameworks.
- Commitment to high-quality, reproducible, and compliant scientific computing practices.
Note
- This job description does not state or imply that these are the only duties to be performed. Employees may be required to perform additional job-related tasks as requested by management.
- All duties and responsibilities are considered essential functions and may be modified to reasonably accommodate individuals with disabilities. This document does not create an employment contract and reflects an at-will employment relationship.