Sr. Software Engineer

QuartzBio Overview:

QuartzBio (www.quartz.bio) is a Software-as-a-Service (SaaS) solutions provider to the life sciences industry. We deliver innovative, data enabling technologies (i.e., software) that provide biotech/pharma (R&D) teams with enterprise-level access to sample/biomarker data management solutions & analytics, information, insight & reporting capabilities.

Our end-to-end (from sample collection to biomarker data) suite of solutions are focused on providing sponsors information (data with context) – we do this by connecting biospecimen, assay as well as clinical data sources in a secure and scalable cloud-based infrastructure, enabling seamless, automated data management workflows, key insight development, improved collaboration, and the ability to make faster, more informed decisions.

Position Summary:

The Senior Software Engineer provides programming and informatics services in support of development, maintenance and testing of Precision’s cutting-edge Biomarker Data Management platform QuartzBio working with an inter-disciplinary team.

Essential functions of the job include but are not limited to:

• Create source code to enhance functionality and usability of web-based user interface
• Develop automated / dynamic processing pipelines for complex data powered by a cloud-based infrastructure
• Manage platform specific help desk requests
• Work independently on moderately complex tasks with minimal guidance
• Collaborate with internal stakeholders and contribute to resolution of complex tasks
• Develop documentation and data specifications
• Perform source code validation and application testing
• Participate in research and development activities as appropriate
• Contribute to the advancement of Precision’s technology-based services in Biomarker Data Management and Translational Informatics
• Other duties as assigned

 

Qualifications:

• Experience:
• Bachelors with 7+ years of experience or Masters with 5+ years of experience; Maximum years of experience required is 10.
• Expertise with Software Development in R and R package development, code version control (Git), software release processes.
• Experience with SQL.
• Familiarity with GNU Make, AWS, Docker.
• Familiarity with challenges in clinical trial sample collection and data management.
• Familiarity with data engineering practices (e.g. data pipelines).
• Ability to translate real-world data collection processes into relational data models.
• Skills:
• Essential:
• Keen ability to identify and simplify complicated code at the level of both the overall design and specific implementation.
• Proficiency with R
• writing robust functions / production-level code
• unit testing (e.g. {testthat})
• debugging
• creating and maintaining R packages
• understanding of and experience with best practices
• version control (git & Gitlab / GitHub)
• Desirable:
• working knowledge of at least one SQL dialect
• make, Docker, Gitlab CI
• experience with R6, S3 OOP in R
• Linux
• data pipelines

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Last updated on Apr 29, 2024