Senior Backend Software Engineer

2 months ago

Montreal, Quebec, Canada Groupe SII Full time
About the Role

Groupe SII is seeking a highly skilled Backend Software Engineer to join our Visualization and Interactive Data Analysis group. As a key member of our team, you will be responsible for designing and developing high-performance systems to transform, analyze, and query large datasets.

Key Responsibilities
  • Develop and Maintain Scalable Systems: Design and implement highly performant systems to process and analyze large datasets, ensuring seamless integration with data visualization interfaces.
  • API Design and Development: Create and maintain APIs to quickly access data from web-based applications, ensuring efficient data exchange and retrieval.
  • Workflow Process Management: Design, implement, and maintain processes to schedule, execute, and monitor data transformation workflows, ensuring optimal system performance.
  • Collaboration and Problem-Solving: Collaborate with computational scientists, biologists, and software engineers to identify and solve complex scientific software engineering challenges.
  • Cloud Infrastructure Management: Manage and maintain cloud infrastructure, including AWS, to establish APIs and data services or databases, ensuring secure and efficient data storage and retrieval.
Requirements
  • Education: Bachelor's degree or higher in Bioinformatics, Computer Science, or related fields.
  • Technical Expertise: 5+ years of experience in Python, designing and developing high-performance systems, and package development.
  • API Development and Maintenance: Expertise in building, deploying, maintaining, and monitoring APIs.
  • Workflow Process Management: Experience with designing, running, and maintaining workflow processes, containers, schedulers, and systems in on-premise servers and the cloud.
  • Cloud Infrastructure: Proficiency with cloud infrastructure, particularly AWS, to establish APIs and data services or databases.
  • Scientific Computing: Experience with scientific computing packages (SciPy, NumPy, pandas, etc.).
  • Best Practices: Demonstrated adherence to best practices in software engineering, including usability, version control, testing, and appropriate use of abstraction.
Nice-to-Haves
  • Formal Build/Release/Deploy Frameworks: Familiarity with formal build/release/deploy and continuous integration frameworks.
  • Kubernetes and FaaS: Experience with Kubernetes, AWS Lambda, and other FaaS or containerized workloads.
  • Data Wrangling and Analysis: Experience with data wrangling, processing, and analysis in Python and/or R.
  • Biological Domain Knowledge: Familiarity with biological domain knowledge, specifically in single-cell genomics.

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