Bioinformatics Software Engineer

About the Role

This is a one-year term position with the possibility of extension, contingent upon work performance and continued funding. The work schedule and location will be set by the department at its discretion and based upon operational needs, with some duties potentially performed at a non-Harvard location.

Key Responsibilities

• 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 modern standards of reproducible code are maintained.
• Design, implement, and maintain bioinformatics pipelines for high-throughput sequencing data (e.g., alignment, QC, variant calling from WGS and RNA-seq).
• 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.
• Develop utility tools for metadata management, file integrity checks, format 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.

Requirements & Tech Stack

• Python and shell scripting
• Next-generation sequencing (NGS) data analysis
• Workflow automation
• Cloud computing and cloud software engineering best practices
• Reproducible code standards
• Docker for reproducible execution environments
• Workflow Description Language (e.g., CWL)
• AWS services (EC2, S3) or similar cloud platforms
• Version Control & CI/CD: Git, automated testing, deployment workflows
• Linux systems
• HPC and distributed computing environments
• Optimizing pipelines for large-scale genomic projects

Qualifications

• Minimum of five years’ post-secondary education or relevant work experience.
• PhD in computational biology, bioinformatics, statistics, CS, or another quantitative field is strongly preferred.
• Superb programming skills and communication skills are strongly preferred.
• Extensive experience with analysis of high-throughput sequencing data.
• Knowledge of bioinformatics tools for sequence alignment, variant calling, sequence data QC, etc.
• Experience with managing multi-omic data (e.g., Illumina/PacBio/ONT Whole Genome Sequencing (WGS), RNA-Seq) is required for the code base supporting the SMaHT Data Analysis Center.