Bioinformatics Engineer (Only for Women)
We are seeking a highly skilled Bioinformatics Engineer with strong expertise in Nextflow and 4+ years of relevant experience to design, develop, and maintain scalable genomics pipelines. This role will focus on building robust, reproducible, and high-performance workflows to support large-scale genomic data analysis in research and production environments.
Key Responsibilities
- Design, develop, and optimize genomics workflows using Nextflow
- Build, deploy, and maintain pipelines for NGS data analysis, including WGS, WES, RNA-Seq, and related applications
- Integrate workflows with cloud platforms and high-performance computing (HPC) environments
- Ensure reproducibility, scalability, reliability, and performance of analytical pipelines
- Collaborate closely with bioinformatics, data science, and research teams to support project requirements
- Troubleshoot, debug, and optimize workflow execution and performance issues
- Develop and maintain technical documentation and workflow best practices
- Implement quality control, validation, and version control standards for pipelines
Minimum 3+ years of experience in bioinformatics, computational biology, or related fields
Qualifications
- Strong hands-on experience in developing and maintaining workflows using Nextflow
- Solid understanding of genomics and NGS data analysis methodologies
- Proficiency in Linux/Unix environments and scripting using Bash and/or Python
- Working knowledge of version control systems and CI/CD practices (Git, GitHub/GitLab)
- Familiarity with container technologies such as Docker and Singularity
- Experience working with cloud platforms (AWS, GCP, Azure) and/or HPC systems
- Experience managing and analyzing large-scale genomic datasets
- Experience in building interactive dashboards for downstream analytics using R Shiny, Python (Streamlit), React, or similar platforms
- Exposure to nf-core pipelines and best practices
- Knowledge of alternative workflow languages such as CWL and WDL
- Prior experience in clinical, regulated, or production genomics environments is a plus