Bioinformatics Engineer (Only for Women)

We are seeking a highly skilled Bioinformatics Engineer with strong expertise in Nextfl ow 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 workfl ows to support large-scale genomic data analysis in research and production environments.

Key Responsibilities

• Design, develop, and optimize genomics workfl ows using Nextfl ow
• Build, deploy, and maintain pipelines for NGS data analysis, including WGS, WES, RNA-Seq, and related applications
• Integrate workfl ows 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 workfl ow 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 fi elds

• Strong hands-on experience in developing and maintaining workfl ows using Nextfl ow
• Solid understanding of genomics and NGS data analysis methodologies
• Profi ciency 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 workfl ow languages such as CWL and WDL
• Prior experience in clinical, regulated, or production genomics environments is a plus