Bioinformatics Engineer

Must Have - Experience with any ggplot2/tidyverse, Plotly, matplot lib, Tableau, d3.js

As a Bioinformatics Engineer, you will work for the world leader in the industry, with a career where you will have the opportunity to collaborate and affect change while expanding your leadership skills and technical knowledge. You can make a real impact in a market that is growing and developing.

• Develop, validate, and implement new software applications, databases, processes, and interfaces relating to next-generation sequencing (NGS) data analysis, advanced diagnostic testing development and validation, data quality review, and clinical reporting.
• Serve as SME on specific systems/workflows supporting advanced development and high-tier production support.
• Prepare reports and other communications of technical activities related to business objectives such as product/process development and improvement.

3+ years of experience with a Bachelor's degree or 1+ year with a Master's degree and experience in an industrial or academic setting working with clinical and biological data or equivalent and underlying technologies including bioinformatic methods, database development, query/scripting/programming languages, cloud development, agile methodology, Dev Ops and other data analysis tools.

• Bioinformatics tools such as Dragen, bwa, VEP, FastQC, Multi
  
  QC, samtools, bedtools.
• Experience with sequencing data analysis, bioinformatics, variant data analysis.
• Pipeline workflow management languages:
  Nextflow (preferred), Cromwell, CWL, etc.
• Cloud Computing: AWS.
• Infrastructure management:
  Terraform, AWS CDK
• Programming
  
  Languages:
  
  Advanced level with interpreted/scripting languages such as Python, JavaScript/typescript, R, etc.
• Containerizing:
  Docker.
• Experience with designing and working with application programming interfaces (e.g. JSON based RESTful APIs).
• Web Frameworks:
  Python Flask, React Native, Bootstrap.
• Reporting:
  Familiarity with R Markdown, Jupyter Notebook.
• Visualization:
  Experience with any ggplot2/tidyverse, Plotly, matplot lib, Tableau, d3.js.
• Source Control:
  Git.
• CI/CD:
  Git Hub CI/CD.
• Familiarity with AI developer tools like Git Hub Copilot.
• Understanding of environment management.
• Experience of working in clinical diagnostics setting (regulations, controlled processes, environment management) is a plus.