Bioinformatics Software Engineer

Job Summary:

Participate in the design of software that supports and enriches research productivity and reliability; implement software solutions.  Develop software and data services with researchers to ensure that modern standards of reproducible code are kept.

Job-Specific Responsibilities:

We are looking for a highly skilled Bioinformatics Software Engineer who specializes in designing, developing, deploying, and maintaining scalable bioinformatics pipelines on cloud-based infrastructure. The candidate will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at the SMaHT Data Analysis Center that manages multi-omic data (e.g., Illumina/PacBio/ONT Whole Genome Sequencing (WGS), RNA-Seq). The ideal candidate will have a deep understanding of next-generation sequencing (NGS) data analysis, workflow automation, cloud computing, and cloud software engineering best practices. This role will support research and production environments where reproducibility, scalability, and performance are critical.

Job Description: 

• Design, implement, and maintain bioinformatics pipelines for high-throughput sequencing data (e.g., alignment, QC, variant calling from WGS and RNA-seq) similar to those in existing repositories: https://github.com/smaht-dac/main-pipelines.
• Build reproducible, well-tested, and automated workflows using workflow management systems (particularly CWL).
• Architect and manage AWS-based compute infrastructure to support pipeline execution, including automated deployment, scaling, and monitoring.
• Containerize workflows using Docker or similar tools for managed execution and portability.
• Integrate CI/CD tooling to automate testing, deployment, and version control to ensure data integrity and correct execution of the pipeline.
• Develop utility tools for metadata management, file integrity checks or conversion (e.g., VCF, BAM to CRAM), and integration with the SMaHT Data Portal.
• Collaborate cross-functionally with research scientists, engineers, and IT teams to refine requirements and deliver high-quality solutions.
• Document code, workflows, and infrastructure configurations clearly.