Ingénieur Automatisation Qa - Software Development Engineer In Test H/F

Contenu de l'offre Ingénieur Automatisation Qa - Software Development Engineer In Test H/F chez Sophia Genetics

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Description
Would you like to join a dynamic and exciting Software Engineering team that uses cutting edge technologies to deliver a world changing product that has a direct impact on the lives of cancer and rare disease patients worldwide? SOPHiA GENETICS (NASDAQ : SOPH)was founded to generate clinically actionable insights from data to improve patient outcomes. Our mission is to provide equal access to medical insights, knowledge, and capabilities by democratizing data-driven medicine.

We observed that across the healthcare ecosystem, a vast amount of digital healthcare data is being generated, fueled by technologies such as next-generation sequencing (\"NGS\"). This data holds promise to accelerate our understanding of biology and disease. However, the data has remained siloed and complex and has not been fully leveraged for the benefit of patients.

We founded SOPHiA GENETICS to change this. Our goal is to empower clinicians and researchers around the world to practice data-driven medicine and improve clinical and scientific outcomes.

In order to grow our engineering team we are looking for a Software Development Engineer in Test (Software Engineer in Test) to join our team in Bidart, France.

Your Mission

You will join our Integration and Release department in a key moment, to drive the migration of our current solutions to microservices and web technologies, following design controls. You will work embedded within a product team that focuses on the Alamut product line and build confidence in its quality.

You will :
- Coordinate with the product team to define test plans for the upcoming projects and releases.
- Translate product requirements into automated or manual test protocols.
- Lead the test plan execution, BE the contact point with the other stakeholders, execute manual tests, and coordinate with the other testers.
- Automate existing manual tests to improve and shorten the release lifecycle.
- Improve visibility on key metrics such as requirement coverage, test coverage, static analysis, etc.
- Spread knowledge on the best practices around software verification and quality engineering across the organization.