Bioinformatics Engineer (Only for Women)

Jobs for Humanity

Bengaluru

On-site

INR 1,500,000 - 2,600,000

Full time

14 days+
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Job summary

Jobs for Humanity is seeking a Bioinformatics Engineer (Only for Women) to design, develop, and maintain scalable genomics pipelines using Nextflow. You will work on WGS, WES, RNA-Seq data and integrate workflows with cloud and HPC environments to enable high-performance analysis in research and production settings.

The role requires 3+ years in bioinformatics or computational biology, strong Linux/Unix, Bash and Python skills, and hands-on Nextflow experience.

Qualifications

  • 3+ years of experience in bioinformatics or computational biology
  • Experience building scalable genomics pipelines with Nextflow
  • Proficiency with Linux/Unix, Bash and Python
  • Experience with version control and CI/CD (Git, GitHub/GitLab)
  • Experience with cloud platforms and/or HPC environments
  • Experience building dashboards for analytics (R Shiny, Streamlit, React) is a plus
  • Exposure to nf-core pipelines and best practices
  • Knowledge of CWL/WDL is a plus
  • Clinical or production genomics experience is a plus

Responsibilities

  • Design, develop, and optimize genomics workflows using Nextflow
  • Build, deploy, and maintain pipelines for NGS data analysis (WGS, WES, RNA-Seq)
  • Integrate workflows with cloud platforms and HPC environments
  • Ensure reproducibility, scalability, reliability, and performance of analytical pipelines
  • Collaborate with bioinformatics, data science, and research teams
  • Troubleshoot and optimize workflow execution and performance
  • Develop and maintain technical documentation and workflow best practices
  • Implement quality control, validation, and version control standards

Skills

Nextflow workflow development
Bioinformatics
Linux/Unix
Python
Bash
Git CI/CD
Cloud/HPC
NGS analysis

Tools

Docker
Singularity
AWS
GCP
Azure

Job description

Bioinformatics Engineer (Only for Women)
  • Full-time

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
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